Pipeline run

{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Azure"
    },
    {
      "is_primary": true,
      "skill_name": "AWS"
    },
    {
      "is_primary": true,
      "skill_name": "Terraform"
    },
    {
      "is_primary": true,
      "skill_name": "CloudFormation"
    },
    {
      "is_primary": true,
      "skill_name": "ARM"
    },
    {
      "is_primary": true,
      "skill_name": "Bicep"
    },
    {
      "is_primary": true,
      "skill_name": "AKS"
    },
    {
      "is_primary": true,
      "skill_name": "EKS"
    },
    {
      "is_primary": true,
      "skill_name": "ECS"
    },
    {
      "is_primary": true,
      "skill_name": "Relational Databases"
    },
    {
      "is_primary": true,
      "skill_name": "CI/CD"
    },
    {
      "is_primary": true,
      "skill_name": "DevSecOps"
    },
    {
      "is_primary": true,
      "skill_name": "Site Reliability Engineering"
    },
    {
      "is_primary": true,
      "skill_name": "Logging"
    },
    {
      "is_primary": true,
      "skill_name": "Metrics"
    },
    {
      "is_primary": true,
      "skill_name": "Distributed Tracing"
    },
    {
      "is_primary": false,
      "skill_name": "ITAR"
    },
    {
      "is_primary": false,
      "skill_name": "EAR"
    },
    {
      "is_primary": false,
      "skill_name": "DFARS"
    }
  ],
  "jd_role": {
    "display_name": "Lead Data Platform Engineer",
    "rationale": null,
    "role_aliases": [
      "Data Engineer",
      "Platform Engineer",
      "Lead Data Engineer"
    ],
    "role_archetype": "Engineering",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": {
      "source_marker": {
        "first_5_words": "As a leading global aerospace",
        "last_5_words": "and integrity."
      },
      "text": "As a leading global aerospace company, Boeing develops, manufactures and services commercial airplanes, defense products and space systems for customers in more than 150 countries. As a top U.S. exporter, the company leverages the talents of a global supplier base to advance economic opportunity, sustainability and community impact. Boeing\u2019s team is committed to innovating for the future, leading with sustainability, and cultivating a culture based on the company\u2019s core values of safety, quality and integrity.",
      "word_count": 64
    },
    "certifications": [],
    "company_name": "Boeing India Private Limited",
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [
          "Aerospace",
          "Defense"
        ],
        "domain": "Aerospace \u0026 Defense"
      },
      "secondary": null
    },
    "education": [
      {
        "level": "Bachelor\u0027s",
        "qualification": "BTECH/BE - Engineering Technology (including Manufacturing Technology) / Computer Science / Data Science / Mathematics / Physics / Chemistry",
        "raw": "Bachelor degree in Engineering, Engineering Technology (including Manufacturing Technology), Computer Science, Data Science, Mathematics, Physics, Chemistry, or non-US equivalent qualifications directly related to the work statement.",
        "requirement": "required"
      }
    ],
    "experience": {
      "max": null,
      "min": null,
      "raw": "Experience in full-stack application development or equivalent systems-software integration roles."
    },
    "job_locations": [
      {
        "aliases": [
          "Bangalore"
        ],
        "city": "Bengaluru",
        "country": "India",
        "state": "Karnataka",
        "work_mode": "null"
      }
    ],
    "role": "Lead Data Platform Engineer",
    "role_aliases": [
      "Data Engineer",
      "Platform Engineer",
      "Lead Data Engineer"
    ],
    "role_archetype": "Engineering",
    "roles_and_responsibilities": [
      {
        "bullet_count": 0,
        "heading": "Position Responsibilities",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "Position Responsibilities : Cloud Engineering",
          "last_5_words": "and recommendations to engineers, stakeholders,"
        },
        "text": "Cloud Engineering \u0026 Platform Enablement\nDesign, deploy, and operate systems across Azure and AWS, including hybrid and multi\u2011cloud environments. Evaluate and select cloud services based on cost, usability, scalability, and long\u2011term maintainability. Implement infrastructure\u2011as\u2011code using Terraform, CloudFormation, ARM, or Bicep to enable repeatable, secure deployments. Support containerized and cloud\u2011native architectures (e.g., AKS, EKS, ECS).\nData\u2011Enabled Engineering\nDesign and optimize relational database schemas and data models supporting both transactional and analytical workloads. Build and integrate data services and pipelines that enable engineers to discover, explore, and reuse test data efficiently. Collaborate with data scientists and analysts to support analytics, visualization, and ML workflows without exposing unnecessary infrastructure complexity.\nDevOps, Reliability \u0026 Security\nBuild CI/CD pipelines and DevSecOps automation to enable rapid, reliable, and secure delivery. Apply Site Reliability Engineering (SRE) practices to ensure system availability, performance, and resilience. Build and maintain observability capabilities\u2014including logging, metrics, and distributed tracing\u2014to enable rapid diagnosis, performance optimization, and operational insight. Contribute to runbooks, incident response, postmortems, and continuous improvement activities.\nCollaboration \u0026 Technical Leadership\nPartner with security and compliance teams to ensure solutions meet Boeing security, data governance, and regulatory requirements (e.g., ITAR, EAR, DFARS). Produce clear technical documentation and operational artifacts. Present technical concepts, findings, and recommendations to engineers, stakeholders, and leadership as needed.",
        "word_count": 335
      }
    ],
    "urls": []
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "ca344d45-7a3f-4b96-9548-86d8e493d216",
  "stage3_signals": {
    "alias_found": true,
    "alias_match_roles": [
      {
        "display_name": "Data Engineer",
        "matched_count": null,
        "role_id": 2,
        "score": 1.0,
        "slug": "data-engineer",
        "total_count": null
      }
    ],
    "kra_match_roles": [
      {
        "display_name": "DevOps Engineer",
        "matched_count": null,
        "role_id": 10,
        "score": 0.5112,
        "slug": "devops-engineer",
        "total_count": null
      },
      {
        "display_name": "Cybersecurity Engineer",
        "matched_count": null,
        "role_id": 5,
        "score": 0.4523,
        "slug": "cybersecurity-engineer",
        "total_count": null
      },
      {
        "display_name": "ML Ops Engineer",
        "matched_count": null,
        "role_id": 16,
        "score": 0.4495,
        "slug": "ml-ops-engineer",
        "total_count": null
      },
      {
        "display_name": "Data Engineer",
        "matched_count": null,
        "role_id": 2,
        "score": 0.4268,
        "slug": "data-engineer",
        "total_count": null
      },
      {
        "display_name": "Cloud Architect",
        "matched_count": null,
        "role_id": 9,
        "score": 0.4198,
        "slug": "cloud-architect",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "DevOps Engineer",
        "matched_count": 8,
        "role_id": 10,
        "score": 0.4211,
        "slug": "devops-engineer",
        "total_count": 19
      },
      {
        "display_name": "Cloud Architect",
        "matched_count": 7,
        "role_id": 9,
        "score": 0.3684,
        "slug": "cloud-architect",
        "total_count": 19
      },
      {
        "display_name": "ML Engineer",
        "matched_count": 4,
        "role_id": 3,
        "score": 0.2105,
        "slug": "ml-engineer",
        "total_count": 19
      },
      {
        "display_name": "AI Engineer",
        "matched_count": 2,
        "role_id": 13,
        "score": 0.1053,
        "slug": "ai-engineer",
        "total_count": 19
      },
      {
        "display_name": "Full Stack Engineer",
        "matched_count": 2,
        "role_id": 15,
        "score": 0.1053,
        "slug": "full-stack-engineer",
        "total_count": 19
      }
    ]
  },
  "stage4_decision": {
    "alias_collision_detected": true,
    "case": "D",
    "chosen_role": {
      "display_name": "DevOps Engineer",
      "matched_count": null,
      "role_id": 10,
      "score": 0.5112,
      "slug": "devops-engineer",
      "total_count": null
    },
    "confidence": 0.9,
    "llm2_fired": true,
    "llm2_reasoning": "The JD\u2019s emphasis on multi-cloud infrastructure design, IaC, CI/CD pipelines, SRE practices, and DevSecOps automation aligns closely with a DevOps Engineer\u2019s core day-to-day responsibilities.",
    "queued": false,
    "reasoning": "LLM2 picked devops-engineer (confidence 0.90)"
  },
  "stage5_updates": {
    "centroid_n_after": 32,
    "centroid_updated": true,
    "collision_log_id": 60,
    "new_kra_attached": null,
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 1345,
        "role_display_name": "DevOps Engineer",
        "role_slug": "devops-engineer",
        "skill_name": "ARM",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1346,
        "role_display_name": "DevOps Engineer",
        "role_slug": "devops-engineer",
        "skill_name": "EKS",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1347,
        "role_display_name": "DevOps Engineer",
        "role_slug": "devops-engineer",
        "skill_name": "DevSecOps",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1348,
        "role_display_name": "DevOps Engineer",
        "role_slug": "devops-engineer",
        "skill_name": "Site Reliability Engineering",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1349,
        "role_display_name": "DevOps Engineer",
        "role_slug": "devops-engineer",
        "skill_name": "Logging",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1350,
        "role_display_name": "DevOps Engineer",
        "role_slug": "devops-engineer",
        "skill_name": "Metrics",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1351,
        "role_display_name": "DevOps Engineer",
        "role_slug": "devops-engineer",
        "skill_name": "Distributed Tracing",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 1352,
        "role_display_name": "DevOps Engineer",
        "role_slug": "devops-engineer",
        "skill_name": "ITAR",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 1353,
        "role_display_name": "DevOps Engineer",
        "role_slug": "devops-engineer",
        "skill_name": "EAR",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 1354,
        "role_display_name": "DevOps Engineer",
        "role_slug": "devops-engineer",
        "skill_name": "DFARS",
        "status": "pending"
      }
    ],
    "queue_entry_id": null,
    "v3_pipeline_triggered": false,
    "v3_role_slug": null,
    "v3_run_id": null
  }
}

{
  "alias_matches": [
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 407,
      "existing_alias_text": "Azure",
      "input_term": "Azure",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "Azure",
        "id": 188,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "azure",
        "sub_category_id": 46,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 406,
      "existing_alias_text": "AWS",
      "input_term": "AWS",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "AWS",
        "id": 187,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "aws",
        "sub_category_id": 46,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 547,
      "existing_alias_text": "Terraform",
      "input_term": "Terraform",
      "matched_canonical": {
        "category_id": 13,
        "display_name": "Terraform",
        "id": 286,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "terraform",
        "sub_category_id": 191,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1382,
      "existing_alias_text": "CloudFormation",
      "input_term": "CloudFormation",
      "matched_canonical": {
        "category_id": 11,
        "display_name": "CloudFormation",
        "id": 837,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CLOUD_SERVICE",
        "slug": "cloudformation",
        "sub_category_id": 181,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1383,
      "existing_alias_text": "Bicep",
      "input_term": "Bicep",
      "matched_canonical": {
        "category_id": 6,
        "display_name": "Bicep",
        "id": 838,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "bicep",
        "sub_category_id": 609,
        "typical_lifespan": "EVERGREEN",
        "volatility": "EMERGING"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1857,
      "existing_alias_text": "AKS",
      "input_term": "AKS",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "AKS",
        "id": 1221,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "aks",
        "sub_category_id": 927,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1402,
      "existing_alias_text": "ECS",
      "input_term": "ECS",
      "matched_canonical": {
        "category_id": 11,
        "display_name": "ECS",
        "id": 854,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CLOUD_SERVICE",
        "slug": "ecs",
        "sub_category_id": 564,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1988,
      "existing_alias_text": "Relational Databases",
      "input_term": "Relational Databases",
      "matched_canonical": {
        "category_id": 37,
        "display_name": "Relational Databases",
        "id": 1345,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "relational-databases",
        "sub_category_id": 1018,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1826,
      "existing_alias_text": "CI/CD",
      "input_term": "CI/CD",
      "matched_canonical": {
        "category_id": 8,
        "display_name": "CI/CD",
        "id": 1190,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "ci-cd",
        "sub_category_id": 900,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
      "alias_persisted": false,
      "existing_alias_id": 1852,
      "existing_alias_text": "DevOps",
      "input_term": "DevSecOps",
      "matched_canonical": {
        "category_id": 8,
        "display_name": "DevOps",
        "id": 1216,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "devops",
        "sub_category_id": 922,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "embedding_alias"
    }
  ],
  "candidate_roles": [
    {
      "display_name": "Backend Engineer",
      "id": 1,
      "rationale": null,
      "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
      "slug": "backend-engineer",
      "source": "db"
    },
    {
      "display_name": "Cybersecurity Engineer",
      "id": 5,
      "rationale": null,
      "role_archetype": null,
      "slug": "cybersecurity-engineer",
      "source": "db"
    },
    {
      "display_name": "Data Engineer",
      "id": 2,
      "rationale": null,
      "role_archetype": null,
      "slug": "data-engineer",
      "source": "db"
    },
    {
      "display_name": "DevOps Engineer",
      "id": 10,
      "rationale": null,
      "role_archetype": null,
      "slug": "devops-engineer",
      "source": "db"
    },
    {
      "display_name": "Full Stack Engineer",
      "id": 15,
      "rationale": null,
      "role_archetype": null,
      "slug": "full-stack-engineer",
      "source": "db"
    },
    {
      "display_name": "ML Engineer",
      "id": 3,
      "rationale": null,
      "role_archetype": null,
      "slug": "ml-engineer",
      "source": "db"
    },
    {
      "display_name": "ML Ops Engineer",
      "id": 16,
      "rationale": null,
      "role_archetype": null,
      "slug": "ml-ops-engineer",
      "source": "db"
    },
    {
      "display_name": "AI Engineer",
      "id": 13,
      "rationale": null,
      "role_archetype": null,
      "slug": "ai-engineer",
      "source": "db"
    },
    {
      "display_name": "Cloud Architect",
      "id": 9,
      "rationale": null,
      "role_archetype": null,
      "slug": "cloud-architect",
      "source": "db"
    }
  ],
  "chosen_role": {
    "display_name": "Cloud Architect",
    "id": 9,
    "rationale": "The primary skills heavily focus on cloud technologies which align with a Cloud Architect\u0027s responsibilities.",
    "role_archetype": null,
    "slug": "cloud-architect",
    "source": "db"
  },
  "dimensions": [
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Platforms",
        "id": 20,
        "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
        "slug": "cloud-platforms",
        "source": "db"
      },
      "input_skill": "Azure",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Backend Engineer",
          "id": 1,
          "rationale": null,
          "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
          "slug": "backend-engineer",
          "source": "db"
        },
        {
          "display_name": "Cybersecurity Engineer",
          "id": 5,
          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
          "source": "db"
        },
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        },
        {
          "display_name": "DevOps Engineer",
          "id": 10,
          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
          "source": "db"
        },
        {
          "display_name": "Full Stack Engineer",
          "id": 15,
          "rationale": null,
          "role_archetype": null,
          "slug": "full-stack-engineer",
          "source": "db"
        },
        {
          "display_name": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        },
        {
          "display_name": "ML Ops Engineer",
          "id": 16,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Platforms \u0026 Managed Services",
        "id": 221,
        "rationale": "Operates and integrates vendor-specific cloud compute, storage, and hosting services.",
        "slug": "cloud-platforms-managed-services",
        "source": "db"
      },
      "input_skill": "Azure",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Full Stack Engineer",
          "id": 15,
          "rationale": null,
          "role_archetype": null,
          "slug": "full-stack-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Platforms for AI Deployment",
        "id": 211,
        "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
        "slug": "cloud-platforms-for-ai-deployment",
        "source": "db"
      },
      "input_skill": "Azure",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "AI Engineer",
          "id": 13,
          "rationale": null,
          "role_archetype": null,
          "slug": "ai-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Provider Platforms",
        "id": 131,
        "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
        "slug": "cloud-provider-platforms",
        "source": "db"
      },
      "input_skill": "Azure",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Security Posture Tools",
        "id": 64,
        "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
        "slug": "cloud-security-posture-tools",
        "source": "db"
      },
      "input_skill": "Azure",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cybersecurity Engineer",
          "id": 5,
          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Platforms",
        "id": 20,
        "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
        "slug": "cloud-platforms",
        "source": "db"
      },
      "input_skill": "AWS",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Backend Engineer",
          "id": 1,
          "rationale": null,
          "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
          "slug": "backend-engineer",
          "source": "db"
        },
        {
          "display_name": "Cybersecurity Engineer",
          "id": 5,
          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
          "source": "db"
        },
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        },
        {
          "display_name": "DevOps Engineer",
          "id": 10,
          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
          "source": "db"
        },
        {
          "display_name": "Full Stack Engineer",
          "id": 15,
          "rationale": null,
          "role_archetype": null,
          "slug": "full-stack-engineer",
          "source": "db"
        },
        {
          "display_name": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        },
        {
          "display_name": "ML Ops Engineer",
          "id": 16,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Platforms for AI Deployment",
        "id": 211,
        "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
        "slug": "cloud-platforms-for-ai-deployment",
        "source": "db"
      },
      "input_skill": "AWS",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "AI Engineer",
          "id": 13,
          "rationale": null,
          "role_archetype": null,
          "slug": "ai-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Provider Platforms",
        "id": 131,
        "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
        "slug": "cloud-provider-platforms",
        "source": "db"
      },
      "input_skill": "AWS",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Security Posture Tools",
        "id": 64,
        "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
        "slug": "cloud-security-posture-tools",
        "source": "db"
      },
      "input_skill": "AWS",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cybersecurity Engineer",
          "id": 5,
          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Infrastructure as Code",
        "id": 132,
        "rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
        "slug": "infrastructure-as-code",
        "source": "db"
      },
      "input_skill": "Terraform",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        },
        {
          "display_name": "DevOps Engineer",
          "id": 10,
          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Infrastructure as Code for ML",
        "id": 57,
        "rationale": "Tools for provisioning and managing ML infrastructure resources through code.",
        "slug": "infrastructure-as-code-for-ml",
        "source": "db"
      },
      "input_skill": "Terraform",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Infrastructure as Code",
        "id": 132,
        "rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
        "slug": "infrastructure-as-code",
        "source": "db"
      },
      "input_skill": "CloudFormation",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        },
        {
          "display_name": "DevOps Engineer",
          "id": 10,
          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Infrastructure as Code",
        "id": 132,
        "rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
        "slug": "infrastructure-as-code",
        "source": "db"
      },
      "input_skill": "Bicep",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        },
        {
          "display_name": "DevOps Engineer",
          "id": 10,
          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Container Orchestration Platforms",
        "id": 134,
        "rationale": "Platforms that schedule and manage containerized workloads across clusters and environments. Cloud Architects need these to define workload placement standards, cluster boundaries, and platform capabilities.",
        "slug": "container-orchestration-platforms",
        "source": "db"
      },
      "input_skill": "AKS",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        },
        {
          "display_name": "DevOps Engineer",
          "id": 10,
          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Container Orchestration Platforms",
        "id": 134,
        "rationale": "Platforms that schedule and manage containerized workloads across clusters and environments. Cloud Architects need these to define workload placement standards, cluster boundaries, and platform capabilities.",
        "slug": "container-orchestration-platforms",
        "source": "db"
      },
      "input_skill": "ECS",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        },
        {
          "display_name": "DevOps Engineer",
          "id": 10,
          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
        "id": 96,
        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "Relational Databases",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "CI/CD Pipeline Platforms",
        "id": 150,
        "rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
        "slug": "ci-cd-pipeline-platforms",
        "source": "db"
      },
      "input_skill": "CI/CD",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "DevOps Engineer",
          "id": 10,
          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "CI/CD for Machine Learning",
        "id": 56,
        "rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
        "slug": "ci-cd-for-machine-learning",
        "source": "db"
      },
      "input_skill": "CI/CD",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "CI/CD Pipeline Platforms",
        "id": 150,
        "rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
        "slug": "ci-cd-pipeline-platforms",
        "source": "db"
      },
      "input_skill": "DevSecOps",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "DevOps Engineer",
          "id": 10,
          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Deployment and Release Patterns",
        "id": 140,
        "rationale": "Patterns for promoting changes safely across environments, including rollout, rollback, and release gating strategies. Cloud Architects define these patterns so teams can deploy consistently across the platform.",
        "slug": "deployment-and-release-patterns",
        "source": "db"
      },
      "input_skill": "DevSecOps",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Infrastructure as Code",
        "id": 132,
        "rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
        "slug": "infrastructure-as-code",
        "source": "db"
      },
      "input_skill": "DevSecOps",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        },
        {
          "display_name": "DevOps Engineer",
          "id": 10,
          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
        "id": 96,
        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "ARM",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Kubernetes for ML Workloads",
        "id": 47,
        "rationale": "Kubernetes-native components used to schedule, accelerate, and isolate ML training and serving workloads. This includes GPU enablement and ML-specific controllers rather than generic cluster administration.",
        "slug": "kubernetes-for-ml-workloads",
        "source": "db"
      },
      "input_skill": "EKS",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        },
        {
          "display_name": "ML Ops Engineer",
          "id": 16,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
        "id": 96,
        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "Site Reliability Engineering",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Observability and Operations",
        "id": 143,
        "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
        "slug": "observability-and-operations",
        "source": "db"
      },
      "input_skill": "Logging",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Observability and Operations",
        "id": 143,
        "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
        "slug": "observability-and-operations",
        "source": "db"
      },
      "input_skill": "Logging",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Experiment Tracking and Evaluation",
        "id": 44,
        "rationale": "Tools and practices for recording experiments, comparing runs, and assessing model quality before release. This dimension focuses on reproducibility, metrics, artifacts, and offline evaluation workflows.",
        "slug": "experiment-tracking-and-evaluation",
        "source": "db"
      },
      "input_skill": "Metrics",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        },
        {
          "display_name": "ML Ops Engineer",
          "id": 16,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Observability and Operations",
        "id": 143,
        "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
        "slug": "observability-and-operations",
        "source": "db"
      },
      "input_skill": "Metrics",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Experiment Tracking and Evaluation",
        "id": 44,
        "rationale": "Tools and practices for recording experiments, comparing runs, and assessing model quality before release. This dimension focuses on reproducibility, metrics, artifacts, and offline evaluation workflows.",
        "slug": "experiment-tracking-and-evaluation",
        "source": "db"
      },
      "input_skill": "Metrics",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        },
        {
          "display_name": "ML Ops Engineer",
          "id": 16,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Observability and Operations",
        "id": 143,
        "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
        "slug": "observability-and-operations",
        "source": "db"
      },
      "input_skill": "Metrics",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Observability and Operations",
        "id": 143,
        "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
        "slug": "observability-and-operations",
        "source": "db"
      },
      "input_skill": "Distributed Tracing",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
        "id": 96,
        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "Distributed Tracing",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Observability and Operations",
        "id": 143,
        "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
        "slug": "observability-and-operations",
        "source": "db"
      },
      "input_skill": "Distributed Tracing",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
        "id": 96,
        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "ITAR",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
        "id": 96,
        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "EAR",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
        "id": 96,
        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "DFARS",
      "llm_role": null,
      "roles_from_db": []
    }
  ],
  "input_final_skills": [
    "Azure",
    "AWS",
    "Terraform",
    "CloudFormation",
    "ARM",
    "Bicep",
    "AKS",
    "EKS",
    "ECS",
    "Relational Databases",
    "CI/CD",
    "DevSecOps",
    "Site Reliability Engineering",
    "Logging",
    "Metrics",
    "Distributed Tracing",
    "ITAR",
    "EAR",
    "DFARS"
  ],
  "input_llm_skills": [
    "Azure",
    "AWS",
    "Terraform",
    "CloudFormation",
    "ARM",
    "Bicep",
    "AKS",
    "EKS",
    "ECS",
    "Relational Databases",
    "CI/CD",
    "DevSecOps",
    "Site Reliability Engineering",
    "Logging",
    "Metrics",
    "Distributed Tracing",
    "ITAR",
    "EAR",
    "DFARS"
  ],
  "new_aliases_persisted": 0,
  "run_id": "ca344d45-7a3f-4b96-9548-86d8e493d216",
  "skills_detail": [
    {
      "aliases_in_db": [
        {
          "alias_text": "Azure",
          "alias_type": "CANONICAL",
          "id": 407,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 9,
        "display_name": "Azure",
        "id": 188,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "azure",
        "sub_category_id": 46,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cloud Platforms",
            "id": 20,
            "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
            "slug": "cloud-platforms",
            "source": "db"
          },
          "input_skill": "Azure",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Backend Engineer",
              "id": 1,
              "rationale": null,
              "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
              "slug": "backend-engineer",
              "source": "db"
            },
            {
              "display_name": "Cybersecurity Engineer",
              "id": 5,
              "rationale": null,
              "role_archetype": null,
              "slug": "cybersecurity-engineer",
              "source": "db"
            },
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            },
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            },
            {
              "display_name": "Full Stack Engineer",
              "id": 15,
              "rationale": null,
              "role_archetype": null,
              "slug": "full-stack-engineer",
              "source": "db"
            },
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "ML Ops Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cloud Platforms \u0026 Managed Services",
            "id": 221,
            "rationale": "Operates and integrates vendor-specific cloud compute, storage, and hosting services.",
            "slug": "cloud-platforms-managed-services",
            "source": "db"
          },
          "input_skill": "Azure",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Full Stack Engineer",
              "id": 15,
              "rationale": null,
              "role_archetype": null,
              "slug": "full-stack-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cloud Platforms for AI Deployment",
            "id": 211,
            "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
            "slug": "cloud-platforms-for-ai-deployment",
            "source": "db"
          },
          "input_skill": "Azure",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "AI Engineer",
              "id": 13,
              "rationale": null,
              "role_archetype": null,
              "slug": "ai-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cloud Provider Platforms",
            "id": 131,
            "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
            "slug": "cloud-provider-platforms",
            "source": "db"
          },
          "input_skill": "Azure",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cloud Security Posture Tools",
            "id": 64,
            "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
            "slug": "cloud-security-posture-tools",
            "source": "db"
          },
          "input_skill": "Azure",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cybersecurity Engineer",
              "id": 5,
              "rationale": null,
              "role_archetype": null,
              "slug": "cybersecurity-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Azure",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "AWS",
          "alias_type": "CANONICAL",
          "id": 406,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 9,
        "display_name": "AWS",
        "id": 187,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "aws",
        "sub_category_id": 46,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cloud Platforms",
            "id": 20,
            "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
            "slug": "cloud-platforms",
            "source": "db"
          },
          "input_skill": "AWS",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Backend Engineer",
              "id": 1,
              "rationale": null,
              "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
              "slug": "backend-engineer",
              "source": "db"
            },
            {
              "display_name": "Cybersecurity Engineer",
              "id": 5,
              "rationale": null,
              "role_archetype": null,
              "slug": "cybersecurity-engineer",
              "source": "db"
            },
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            },
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            },
            {
              "display_name": "Full Stack Engineer",
              "id": 15,
              "rationale": null,
              "role_archetype": null,
              "slug": "full-stack-engineer",
              "source": "db"
            },
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "ML Ops Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cloud Platforms for AI Deployment",
            "id": 211,
            "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
            "slug": "cloud-platforms-for-ai-deployment",
            "source": "db"
          },
          "input_skill": "AWS",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "AI Engineer",
              "id": 13,
              "rationale": null,
              "role_archetype": null,
              "slug": "ai-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cloud Provider Platforms",
            "id": 131,
            "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
            "slug": "cloud-provider-platforms",
            "source": "db"
          },
          "input_skill": "AWS",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cloud Security Posture Tools",
            "id": 64,
            "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
            "slug": "cloud-security-posture-tools",
            "source": "db"
          },
          "input_skill": "AWS",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cybersecurity Engineer",
              "id": 5,
              "rationale": null,
              "role_archetype": null,
              "slug": "cybersecurity-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "AWS",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Terraform",
          "alias_type": "CANONICAL",
          "id": 547,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 13,
        "display_name": "Terraform",
        "id": 286,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "terraform",
        "sub_category_id": 191,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Infrastructure as Code",
            "id": 132,
            "rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
            "slug": "infrastructure-as-code",
            "source": "db"
          },
          "input_skill": "Terraform",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            },
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Infrastructure as Code for ML",
            "id": 57,
            "rationale": "Tools for provisioning and managing ML infrastructure resources through code.",
            "slug": "infrastructure-as-code-for-ml",
            "source": "db"
          },
          "input_skill": "Terraform",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Terraform",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "CloudFormation",
          "alias_type": "CANONICAL",
          "id": 1382,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 11,
        "display_name": "CloudFormation",
        "id": 837,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CLOUD_SERVICE",
        "slug": "cloudformation",
        "sub_category_id": 181,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Infrastructure as Code",
            "id": 132,
            "rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
            "slug": "infrastructure-as-code",
            "source": "db"
          },
          "input_skill": "CloudFormation",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            },
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "CloudFormation",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "React Frontend Development",
            "id": 96,
            "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
            "slug": "d_init_01",
            "source": "db"
          },
          "input_skill": "ARM",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "ARM",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Architecture",
          "skill_nature": "PATTERN",
          "sub_category": "instruction_set_architecture",
          "typical_lifespan": "EVERGREEN",
          "version_strategy": "SEPARATE_ENTITY",
          "volatility": "STABLE"
        },
        "enrichment": {
          "ambiguity": {
            "ambiguity_flag": true,
            "confused_with": [
              "arm64",
              "aarch64"
            ],
            "reasoning": "\u201cARM\u201d in JDs can refer broadly to ARM architecture or specifically to ARM64/AArch64 targets, which are distinct catalog skills."
          },
          "context_keywords": {
            "context_keywords": [
              "ARM Cortex",
              "ARMv7",
              "ARMv8",
              "assembly language",
              "RISC",
              "embedded systems",
              "SoC",
              "microcontroller",
              "NEON",
              "Thumb",
              "JTAG",
              "debugging",
              "low-level programming",
              "cross-compilation",
              "hardware abstraction",
              "real-time operating systems"
            ]
          },
          "maturity": {
            "confidence": 0.93,
            "maturity": "well_known",
            "reasoning": "ARM is a dominant instruction-set architecture in mobile, embedded, and increasingly server/cloud chips; job postings commonly mention ARM64/AArch64 alongside Linux and systems work."
          },
          "skill_id": "arm",
          "vendor_license": {
            "confidence": 0.9,
            "license": null,
            "vendor": null,
            "year_introduced": null
          },
          "versioning": {
            "current_version": "ARMv8-A",
            "version_aliases": {
              "AArch64": "ARMv8-A",
              "ARMv8": "ARMv8-A",
              "arm64": "ARMv8-A"
            },
            "versioned": true
          }
        },
        "keep_log": [],
        "locked_dimensions": [
          {
            "description": "Low-level ARM CPU architecture, instruction set, and assembly-level programming for ARM-based systems. This fits ARM because the skill can refer to the ARM ISA and the platform-specific programming model rather than a higher-level framework.",
            "exemplar_skills": [
              "ARM",
              "ARM assembly",
              "ARM instruction set",
              "AArch64",
              "AArch32",
              "ARMv8",
              "register allocation on ARM",
              "calling conventions on ARM"
            ],
            "in_scope": "ARM, ARM instruction set, ARM assembly, registers and calling conventions, memory addressing modes, condition codes, ARMv7, ARMv8, AArch32, AArch64, NEON basics, low-level debugging on ARM",
            "name": "ARM Architecture and Assembly",
            "out_of_scope": "ARM-based cloud instances and hardware selection, mobile app development for ARM devices, compiler toolchains and cross-compilation workflows, GPU or accelerator programming",
            "overlap_flags": [
              {
                "reason": "ARM may also refer to ARM-based cloud hardware or instance families, which belongs to cloud platform knowledge rather than ISA-level architecture.",
                "with_dim_id": "cloud-platforms",
                "with_dim_name": null,
                "with_role": "Backend Engineer, Cybersecurity Engineer, Data Engineer, DevOps Engineer, Full Stack Engineer, ML Engineer, ML Ops Engineer"
              },
              {
                "reason": "Cross-compiling for ARM can involve build tooling, but the core skill here is the ARM architecture itself.",
                "with_dim_id": "build-and-packaging-tooling",
                "with_dim_name": null,
                "with_role": "DevOps Engineer"
              }
            ],
            "tentative_id": "d_init_01"
          }
        ],
        "merge_log": [],
        "placed": {
          "name": "ARM",
          "placement_confidence": 0.92,
          "primary_dimension": "d_init_01",
          "reasoning": "Deterministic JD placement: locked_dimensions has 1 dimension(s) from skill-driven dimension generation after reconciliation; primary_dimension is the first locked dim.",
          "secondary_dimensions": [],
          "skill_id": "arm"
        },
        "relationships": {
          "child_skills": [],
          "parent_skills": [],
          "related_to": [],
          "requires": [],
          "skill_id": "arm",
          "suppress_on_match": []
        },
        "skill_id": "arm",
        "split_log": [],
        "typed": {
          "alternatives_considered": [],
          "confidence": 0.91,
          "name": "ARM",
          "reasoning": "ARM is fundamentally an instruction set architecture, so it fits the Architecture category rather than a tool, platform, or language.",
          "skill_id": "arm",
          "subtype": "instruction_set_architecture",
          "type": "Architecture"
        },
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Bicep",
          "alias_type": "CANONICAL",
          "id": 1383,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 6,
        "display_name": "Bicep",
        "id": 838,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "bicep",
        "sub_category_id": 609,
        "typical_lifespan": "EVERGREEN",
        "volatility": "EMERGING"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Infrastructure as Code",
            "id": 132,
            "rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
            "slug": "infrastructure-as-code",
            "source": "db"
          },
          "input_skill": "Bicep",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            },
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Bicep",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "AKS",
          "alias_type": "CANONICAL",
          "id": 1857,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 9,
        "display_name": "AKS",
        "id": 1221,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "aks",
        "sub_category_id": 927,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Container Orchestration Platforms",
            "id": 134,
            "rationale": "Platforms that schedule and manage containerized workloads across clusters and environments. Cloud Architects need these to define workload placement standards, cluster boundaries, and platform capabilities.",
            "slug": "container-orchestration-platforms",
            "source": "db"
          },
          "input_skill": "AKS",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            },
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "AKS",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Kubernetes for ML Workloads",
            "id": 47,
            "rationale": "Kubernetes-native components used to schedule, accelerate, and isolate ML training and serving workloads. This includes GPU enablement and ML-specific controllers rather than generic cluster administration.",
            "slug": "kubernetes-for-ml-workloads",
            "source": "db"
          },
          "input_skill": "EKS",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "ML Ops Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "EKS",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Platform",
          "skill_nature": "PLATFORM",
          "sub_category": "kubernetes_platform",
          "typical_lifespan": "EVERGREEN",
          "version_strategy": "NOT_APPLICABLE",
          "volatility": "STABLE"
        },
        "enrichment": {
          "ambiguity": {
            "ambiguity_flag": true,
            "confused_with": [
              "kubernetes",
              "eksctl"
            ],
            "reasoning": "\u201cEKS\u201d can be confused with generic Kubernetes mentions or related AWS tooling like eksctl in JDs."
          },
          "context_keywords": {
            "context_keywords": [
              "Kubernetes",
              "AWS",
              "Helm",
              "kubectl",
              "ECR",
              "Fargate",
              "CloudFormation",
              "CI/CD",
              "microservices",
              "container orchestration",
              "service mesh",
              "monitoring",
              "scalability",
              "load balancing",
              "network policies"
            ]
          },
          "maturity": {
            "confidence": 0.93,
            "maturity": "well_known",
            "reasoning": "Amazon EKS appears in many cloud/Kubernetes job postings and is a standard managed Kubernetes option on AWS, with strong vendor docs and ecosystem adoption."
          },
          "skill_id": "eks",
          "vendor_license": {
            "confidence": 0.9,
            "license": "unknown",
            "vendor": "Amazon",
            "year_introduced": 2018
          },
          "versioning": {
            "current_version": null,
            "version_aliases": {},
            "versioned": false
          }
        },
        "keep_log": [],
        "locked_dimensions": [
          {
            "description": "Kubernetes-based scheduling and runtime management for containerized workloads. EKS belongs here because it is AWS\u0027s managed Kubernetes service and is used to run, scale, and isolate workloads on Kubernetes clusters.",
            "exemplar_skills": [
              "EKS",
              "Kubernetes",
              "kubectl",
              "Helm",
              "Kubernetes operators",
              "pod scheduling",
              "cluster autoscaling"
            ],
            "in_scope": "EKS, Kubernetes clusters, pods, deployments, daemonsets, statefulsets, services, ingress, node groups, autoscaling, GPU scheduling, workload isolation",
            "name": "Kubernetes Workload Orchestration",
            "out_of_scope": "AWS account governance, IAM policy design, VPC networking, load balancer setup, and other cloud-provider primitives owned by cloud platform or identity/networking dimensions",
            "overlap_flags": [
              {
                "reason": "EKS is an AWS-managed service, so it overlaps with general cloud platform knowledge even though the core skill is Kubernetes-centric.",
                "with_dim_id": "cloud-platforms",
                "with_dim_name": null,
                "with_role": "Backend Engineer, Cybersecurity Engineer, Data Engineer, DevOps Engineer, Full Stack Engineer, ML Engineer, ML Ops Engineer"
              },
              {
                "reason": "EKS deployments often require cluster hardening, admission controls, and runtime security policies.",
                "with_dim_id": "container-and-kubernetes-security",
                "with_dim_name": null,
                "with_role": "Cybersecurity Engineer"
              }
            ],
            "tentative_id": "kubernetes-for-ml-workloads"
          }
        ],
        "merge_log": [],
        "placed": {
          "name": "EKS",
          "placement_confidence": 0.92,
          "primary_dimension": "kubernetes-for-ml-workloads",
          "reasoning": "Deterministic JD placement: locked_dimensions has 1 dimension(s) from skill-driven dimension generation after reconciliation; primary_dimension is the first locked dim.",
          "secondary_dimensions": [],
          "skill_id": "eks"
        },
        "relationships": {
          "child_skills": [],
          "parent_skills": [
            "kubernetes",
            "aws-ec2"
          ],
          "related_to": [
            "kserve",
            "fsdp",
            "sops",
            "elk",
            "enterprise-saas"
          ],
          "requires": [],
          "skill_id": "eks",
          "suppress_on_match": []
        },
        "skill_id": "eks",
        "split_log": [],
        "typed": {
          "alternatives_considered": [],
          "confidence": 0.97,
          "name": "EKS",
          "reasoning": "By the Platform vs Tool rule, EKS is a hosted multi-tenant managed Kubernetes environment with APIs rather than software you run yourself, so it is a Platform.",
          "skill_id": "eks",
          "subtype": "kubernetes_platform",
          "type": "Platform"
        },
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "ECS",
          "alias_type": "CANONICAL",
          "id": 1402,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 11,
        "display_name": "ECS",
        "id": 854,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CLOUD_SERVICE",
        "slug": "ecs",
        "sub_category_id": 564,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Container Orchestration Platforms",
            "id": 134,
            "rationale": "Platforms that schedule and manage containerized workloads across clusters and environments. Cloud Architects need these to define workload placement standards, cluster boundaries, and platform capabilities.",
            "slug": "container-orchestration-platforms",
            "source": "db"
          },
          "input_skill": "ECS",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            },
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "ECS",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Relational Databases",
          "alias_type": "CANONICAL",
          "id": 1988,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 37,
        "display_name": "Relational Databases",
        "id": 1345,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "relational-databases",
        "sub_category_id": 1018,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "React Frontend Development",
            "id": 96,
            "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
            "slug": "d_init_01",
            "source": "db"
          },
          "input_skill": "Relational Databases",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "Relational Databases",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "CI/CD",
          "alias_type": "CANONICAL",
          "id": 1826,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 8,
        "display_name": "CI/CD",
        "id": 1190,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "ci-cd",
        "sub_category_id": 900,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "CI/CD Pipeline Platforms",
            "id": 150,
            "rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
            "slug": "ci-cd-pipeline-platforms",
            "source": "db"
          },
          "input_skill": "CI/CD",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "CI/CD for Machine Learning",
            "id": 56,
            "rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
            "slug": "ci-cd-for-machine-learning",
            "source": "db"
          },
          "input_skill": "CI/CD",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "CI/CD",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "DevOps",
          "alias_type": "CANONICAL",
          "id": 1852,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 8,
        "display_name": "DevOps",
        "id": 1216,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "devops",
        "sub_category_id": 922,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "CI/CD Pipeline Platforms",
            "id": 150,
            "rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
            "slug": "ci-cd-pipeline-platforms",
            "source": "db"
          },
          "input_skill": "DevSecOps",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Deployment and Release Patterns",
            "id": 140,
            "rationale": "Patterns for promoting changes safely across environments, including rollout, rollback, and release gating strategies. Cloud Architects define these patterns so teams can deploy consistently across the platform.",
            "slug": "deployment-and-release-patterns",
            "source": "db"
          },
          "input_skill": "DevSecOps",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Infrastructure as Code",
            "id": 132,
            "rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
            "slug": "infrastructure-as-code",
            "source": "db"
          },
          "input_skill": "DevSecOps",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            },
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "DevSecOps",
      "matched_via": "embedding_alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "React Frontend Development",
            "id": 96,
            "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
            "slug": "d_init_01",
            "source": "db"
          },
          "input_skill": "Site Reliability Engineering",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "Site Reliability Engineering",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Methodology",
          "skill_nature": "METHODOLOGY",
          "sub_category": "site_reliability_engineering",
          "typical_lifespan": "EVERGREEN",
          "version_strategy": "NOT_APPLICABLE",
          "volatility": "STABLE"
        },
        "enrichment": {
          "ambiguity": {
            "ambiguity_flag": false,
            "confused_with": [],
            "reasoning": "\u201cSite Reliability Engineering\u201d is a specific, widely used discipline name; unlikely to be confused with another distinct catalog skill in typical JDs."
          },
          "context_keywords": {
            "context_keywords": [
              "monitoring",
              "incident response",
              "SLO",
              "SLA",
              "error budget",
              "chaos engineering",
              "automation",
              "observability",
              "resilience",
              "load balancing",
              "capacity planning",
              "DevOps",
              "Kubernetes",
              "microservices",
              "cloud infrastructure"
            ]
          },
          "maturity": {
            "confidence": 0.96,
            "maturity": "well_known",
            "reasoning": "SRE is a hiring-pipeline staple: job boards and LinkedIn show many roles explicitly asking for Site Reliability Engineering, and major vendors like Google, AWS, and Datadog publish SRE guidance and tooling around it."
          },
          "skill_id": "site-reliability-engineering",
          "vendor_license": {
            "confidence": 0.95,
            "license": null,
            "vendor": null,
            "year_introduced": null
          },
          "versioning": {
            "current_version": null,
            "version_aliases": {},
            "versioned": false
          }
        },
        "keep_log": [],
        "locked_dimensions": [
          {
            "description": "Practices for operating production systems with high availability, fast recovery, and controlled change. This covers reliability engineering work such as SLOs, incident management, capacity planning, and automation, which is exactly what Site Reliability Engineering refers to.",
            "exemplar_skills": [
              "Site Reliability Engineering",
              "SLO design",
              "SLI monitoring",
              "error budget management",
              "incident management",
              "postmortems",
              "capacity planning",
              "toil reduction",
              "production readiness reviews"
            ],
            "in_scope": "Site Reliability Engineering, SRE practices, service level objectives (SLOs), service level indicators (SLIs), error budgets, incident management, on-call operations, postmortems, capacity planning, toil reduction, reliability automation, production readiness reviews",
            "name": "Site Reliability Engineering",
            "out_of_scope": "Application feature development, model training and evaluation, cloud provider selection, container security policy, which belong to product engineering, ML engineering, cloud platforms, or security dimensions",
            "overlap_flags": [
              {
                "reason": "SRE relies heavily on monitoring, logging, and tracing, but this dimension is broader operational observability rather than reliability engineering specifically.",
                "with_dim_id": "observability-and-operations",
                "with_dim_name": null,
                "with_role": "Cloud Architect"
              },
              {
                "reason": "Both touch incident handling, but SRE includes ongoing reliability ownership, SLOs, and prevention work beyond incident support.",
                "with_dim_id": "incident-response-support",
                "with_dim_name": null,
                "with_role": "ML Ops Engineer"
              }
            ],
            "tentative_id": "d_init_01"
          }
        ],
        "merge_log": [],
        "placed": {
          "name": "Site Reliability Engineering",
          "placement_confidence": 0.92,
          "primary_dimension": "d_init_01",
          "reasoning": "Deterministic JD placement: locked_dimensions has 1 dimension(s) from skill-driven dimension generation after reconciliation; primary_dimension is the first locked dim.",
          "secondary_dimensions": [],
          "skill_id": "site-reliability-engineering"
        },
        "relationships": {
          "child_skills": [],
          "parent_skills": [],
          "related_to": [
            "observability",
            "failure-analysis",
            "sdlc",
            "evaluation",
            "sops",
            "enterprise-saas"
          ],
          "requires": [],
          "skill_id": "site-reliability-engineering",
          "suppress_on_match": []
        },
        "skill_id": "site-reliability-engineering",
        "split_log": [],
        "typed": {
          "alternatives_considered": [],
          "confidence": 0.94,
          "name": "Site Reliability Engineering",
          "reasoning": "Site Reliability Engineering is fundamentally a way of working for operating and improving systems, so by the Concept vs Methodology rule it fits Methodology rather than a Concept or Architecture.",
          "skill_id": "site-reliability-engineering",
          "subtype": "site_reliability_engineering",
          "type": "Methodology"
        },
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Observability and Operations",
            "id": 143,
            "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
            "slug": "observability-and-operations",
            "source": "db"
          },
          "input_skill": "Logging",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Observability and Operations",
            "id": 143,
            "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
            "slug": "observability-and-operations",
            "source": "db"
          },
          "input_skill": "Logging",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Logging",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Concept",
          "skill_nature": "CONCEPT",
          "sub_category": "observability_concept",
          "typical_lifespan": "EVERGREEN",
          "version_strategy": "NOT_APPLICABLE",
          "volatility": "STABLE"
        },
        "enrichment": {
          "ambiguity": {
            "ambiguity_flag": false,
            "confused_with": [],
            "reasoning": "\u201cLogging\u201d is a standard observability concept and is unlikely to be confused with other distinct catalog skills."
          },
          "context_keywords": {
            "context_keywords": [
              "log aggregation",
              "log analysis",
              "structured logging",
              "log management",
              "ELK stack",
              "log monitoring",
              "centralized logging",
              "log retention",
              "log parsing",
              "observability",
              "tracing",
              "debugging",
              "alerting",
              "performance metrics",
              "audit logs"
            ]
          },
          "maturity": {
            "confidence": 0.97,
            "maturity": "well_known",
            "reasoning": "Logging is a standard requirement in most software JDs and observability stacks; vendors like Datadog, Splunk, and ELK/Elastic market log ingestion as core platform capability."
          },
          "skill_id": "logging",
          "vendor_license": {
            "confidence": 1.0,
            "license": null,
            "vendor": null,
            "year_introduced": null
          },
          "versioning": {
            "current_version": null,
            "version_aliases": {},
            "versioned": false
          }
        },
        "keep_log": [
          {
            "a_dim_id": "observability-and-operations",
            "a_name": "Observability and Operations",
            "a_role": "__skill_focal__",
            "b_dim_id": "observability-and-operations",
            "b_name": "Observability and Operations",
            "b_role": "Cloud Architect",
            "pair_kind": "cross_role",
            "reasoning": "Dim A is logging-centric operational telemetry: structured logs, aggregation, retention, search, correlation, shipping, and audit/application/infrastructure logs. Dim B is cloud-architecture observability and operational readiness: monitoring, logging, tracing, and defining what telemetry/controls workloads must expose. A senior practitioner in A would not naturally be a senior practitioner in B. career-track: no, because log-platform/telemetry engineering is different from cloud architecture observability/readiness design.",
            "similarity": 0.706900887779069
          }
        ],
        "locked_dimensions": [
          {
            "description": "Operational telemetry used to understand system behavior, diagnose issues, and support production reliability. Logging belongs here because it is a core signal for troubleshooting, auditability, and day-to-day platform operations.",
            "exemplar_skills": [
              "Logging",
              "Structured Logging",
              "Log Aggregation",
              "Log Retention",
              "Log Search",
              "Log Correlation",
              "Centralized Logging"
            ],
            "in_scope": "Logging, structured logs, log aggregation, log retention, log search, log correlation, log shipping, centralized logging, application logs, infrastructure logs, audit logs",
            "name": "Observability and Operations",
            "out_of_scope": "Metrics collection, distributed tracing, alerting rules, incident management, these are adjacent observability concerns owned by other telemetry or operations dimensions",
            "overlap_flags": [
              {
                "reason": "Logs are heavily used during incident triage, but that dimension focuses on response workflow rather than telemetry design.",
                "with_dim_id": "incident-response-support",
                "with_dim_name": null,
                "with_role": "ML Ops Engineer"
              },
              {
                "reason": "Logging supports troubleshooting and triage, though this dimension is more about operational diagnosis than log instrumentation itself.",
                "with_dim_id": "observability-and-incident-triage",
                "with_dim_name": null,
                "with_role": "DevOps Engineer"
              }
            ],
            "tentative_id": "observability-and-operations"
          },
          {
            "description": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
            "exemplar_skills": [
              "Observability and Operations"
            ],
            "in_scope": "Skills, tools, and practices that belong under Observability and Operations for the target role, including items implied by the dimension rationale.",
            "name": "Observability and Operations",
            "out_of_scope": "Adjacent clusters explicitly not owned by Observability and Operations, including unrelated platforms, roles, and skill families per library policy.",
            "overlap_flags": [],
            "tentative_id": "observability-and-operations"
          }
        ],
        "merge_log": [],
        "placed": {
          "name": "Logging",
          "placement_confidence": 0.92,
          "primary_dimension": "observability-and-operations",
          "reasoning": "Deterministic JD placement: locked_dimensions has 2 dimension(s) from skill-driven dimension generation after reconciliation; primary_dimension is the first locked dim.",
          "secondary_dimensions": [],
          "skill_id": "logging"
        },
        "relationships": {
          "child_skills": [],
          "parent_skills": [
            "observability"
          ],
          "related_to": [
            "artifact-logging",
            "recording",
            "evaluation",
            "authentication",
            "api",
            "sync",
            "context-management",
            "backfills"
          ],
          "requires": [],
          "skill_id": "logging",
          "suppress_on_match": []
        },
        "skill_id": "logging",
        "split_log": [],
        "typed": {
          "alternatives_considered": [],
          "confidence": 0.9,
          "name": "Logging",
          "reasoning": "Logging is fundamentally a knowledge unit about recording and inspecting system events, so it fits the Concept type rather than a tool, format, or methodology.",
          "skill_id": "logging",
          "subtype": "observability_concept",
          "type": "Concept"
        },
        "warnings": [
          "stage3_post_filter_dropped_catalog_only_locked_dims:41-\u003e2"
        ]
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Experiment Tracking and Evaluation",
            "id": 44,
            "rationale": "Tools and practices for recording experiments, comparing runs, and assessing model quality before release. This dimension focuses on reproducibility, metrics, artifacts, and offline evaluation workflows.",
            "slug": "experiment-tracking-and-evaluation",
            "source": "db"
          },
          "input_skill": "Metrics",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "ML Ops Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Observability and Operations",
            "id": 143,
            "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
            "slug": "observability-and-operations",
            "source": "db"
          },
          "input_skill": "Metrics",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Experiment Tracking and Evaluation",
            "id": 44,
            "rationale": "Tools and practices for recording experiments, comparing runs, and assessing model quality before release. This dimension focuses on reproducibility, metrics, artifacts, and offline evaluation workflows.",
            "slug": "experiment-tracking-and-evaluation",
            "source": "db"
          },
          "input_skill": "Metrics",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "ML Ops Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Observability and Operations",
            "id": 143,
            "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
            "slug": "observability-and-operations",
            "source": "db"
          },
          "input_skill": "Metrics",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Metrics",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Concept",
          "skill_nature": "CONCEPT",
          "sub_category": "observability_metrics",
          "typical_lifespan": "EVERGREEN",
          "version_strategy": "NOT_APPLICABLE",
          "volatility": "STABLE"
        },
        "enrichment": {
          "ambiguity": {
            "ambiguity_flag": true,
            "confused_with": [
              "monitoring",
              "kpis"
            ],
            "reasoning": "\u201cMetrics\u201d in JDs can refer broadly to monitoring/observability or business KPIs, not just experiment tracking and evaluation."
          },
          "context_keywords": {
            "context_keywords": [
              "KPI",
              "dashboard",
              "data visualization",
              "monitoring",
              "analytics",
              "performance indicators",
              "A/B testing",
              "data-driven",
              "real-time metrics",
              "event tracking",
              "user engagement",
              "reporting tools",
              "business intelligence",
              "metric collection",
              "observability",
              "data analysis"
            ]
          },
          "maturity": {
            "confidence": 0.93,
            "maturity": "well_known",
            "reasoning": "Metrics are a standard observability requirement and appear in many SRE/DevOps/Platform job descriptions; major vendors like Prometheus/Grafana and cloud monitoring services reinforce broad adoption."
          },
          "skill_id": "metrics",
          "vendor_license": {
            "confidence": 0.95,
            "license": null,
            "vendor": null,
            "year_introduced": null
          },
          "versioning": {
            "current_version": null,
            "version_aliases": {},
            "versioned": false
          }
        },
        "keep_log": [],
        "locked_dimensions": [
          {
            "description": "Tools and practices for recording runs, comparing results, and assessing model quality before release. Metrics belongs here because model and experiment metrics are the core signals used to judge training and evaluation outcomes.",
            "exemplar_skills": [
              "Metrics",
              "experiment tracking",
              "evaluation metrics",
              "run comparison",
              "MLflow",
              "Weights \u0026 Biases",
              "model validation"
            ],
            "in_scope": "Metrics, experiment metrics, evaluation metrics, run comparison, model quality scoring, validation metrics, training curves, offline evaluation, A/B comparison of runs, MLflow metrics, Weights \u0026 Biases charts",
            "name": "Experiment Tracking and Evaluation",
            "out_of_scope": "Production monitoring dashboards, service SLOs, alerting, and infrastructure telemetry, which belong to observability and operations dimensions; governance reporting and compliance evidence, which belong to AI governance dimensions",
            "overlap_flags": [
              {
                "reason": "The word metrics can also mean production telemetry, but this dimension is specifically about model and experiment evaluation.",
                "with_dim_id": "observability-and-operations",
                "with_dim_name": null,
                "with_role": "Cloud Architect"
              }
            ],
            "tentative_id": "experiment-tracking-and-evaluation"
          },
          {
            "description": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Metrics belongs here when it refers to production telemetry used to understand system health and performance.",
            "exemplar_skills": [
              "Metrics",
              "Prometheus",
              "Grafana",
              "SLIs",
              "SLOs",
              "alerting",
              "dashboards"
            ],
            "in_scope": "Metrics, dashboards, alerts, SLIs, SLOs, service telemetry, Prometheus metrics, Grafana dashboards, log aggregation, tracing, operational monitoring",
            "name": "Observability and Operations",
            "out_of_scope": "Model evaluation scores, experiment comparison, and training diagnostics, which are owned by experiment tracking and evaluation; incident command procedures, which belong to incident response support",
            "overlap_flags": [
              {
                "reason": "Metrics is also used for ML experiment evaluation, but this dimension covers production observability rather than model assessment.",
                "with_dim_id": "experiment-tracking-and-evaluation",
                "with_dim_name": null,
                "with_role": "ML Engineer, ML Ops Engineer"
              }
            ],
            "tentative_id": "observability-and-operations"
          },
          {
            "description": "Tools and practices for recording experiments, comparing runs, and assessing model quality before release. This dimension focuses on reproducibility, metrics, artifacts, and offline evaluation workflows.",
            "exemplar_skills": [
              "Experiment Tracking and Evaluation"
            ],
            "in_scope": "Skills, tools, and practices that belong under Experiment Tracking and Evaluation for the target role, including items implied by the dimension rationale.",
            "name": "Experiment Tracking and Evaluation",
            "out_of_scope": "Adjacent clusters explicitly not owned by Experiment Tracking and Evaluation, including unrelated platforms, roles, and skill families per library policy.",
            "overlap_flags": [],
            "tentative_id": "experiment-tracking-and-evaluation"
          },
          {
            "description": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
            "exemplar_skills": [
              "Observability and Operations"
            ],
            "in_scope": "Skills, tools, and practices that belong under Observability and Operations for the target role, including items implied by the dimension rationale.",
            "name": "Observability and Operations",
            "out_of_scope": "Adjacent clusters explicitly not owned by Observability and Operations, including unrelated platforms, roles, and skill families per library policy.",
            "overlap_flags": [],
            "tentative_id": "observability-and-operations"
          }
        ],
        "merge_log": [],
        "placed": {
          "name": "Metrics",
          "placement_confidence": 0.92,
          "primary_dimension": "experiment-tracking-and-evaluation",
          "reasoning": "Deterministic JD placement: locked_dimensions has 4 dimension(s) from skill-driven dimension generation after reconciliation; primary_dimension is the first locked dim.",
          "secondary_dimensions": [
            "observability-and-operations"
          ],
          "skill_id": "metrics"
        },
        "relationships": {
          "child_skills": [],
          "parent_skills": [
            "observability"
          ],
          "related_to": [
            "artifact-logging",
            "weights-biases",
            "weights-biases-runs",
            "sync",
            "api",
            "pagination"
          ],
          "requires": [
            "evaluation"
          ],
          "skill_id": "metrics",
          "suppress_on_match": []
        },
        "skill_id": "metrics",
        "split_log": [],
        "typed": {
          "alternatives_considered": [],
          "confidence": 0.91,
          "name": "Metrics",
          "reasoning": "Metrics is fundamentally a knowledge unit about measuring system behavior, so by the Concept vs Methodology rule it is a Concept rather than a tool or format.",
          "skill_id": "metrics",
          "subtype": "observability_metrics",
          "type": "Concept"
        },
        "warnings": [
          "stage3_post_filter_dropped_catalog_only_locked_dims:42-\u003e4"
        ]
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Observability and Operations",
            "id": 143,
            "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
            "slug": "observability-and-operations",
            "source": "db"
          },
          "input_skill": "Distributed Tracing",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "React Frontend Development",
            "id": 96,
            "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
            "slug": "d_init_01",
            "source": "db"
          },
          "input_skill": "Distributed Tracing",
          "llm_role": null,
          "roles_from_db": []
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Observability and Operations",
            "id": 143,
            "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
            "slug": "observability-and-operations",
            "source": "db"
          },
          "input_skill": "Distributed Tracing",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Distributed Tracing",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Concept",
          "skill_nature": "CONCEPT",
          "sub_category": "observability_concept",
          "typical_lifespan": "EVERGREEN",
          "version_strategy": "NOT_APPLICABLE",
          "volatility": "STABLE"
        },
        "enrichment": {
          "ambiguity": {
            "ambiguity_flag": false,
            "confused_with": [],
            "reasoning": "\u201cDistributed Tracing\u201d is a specific observability concept (spans/trace IDs) and is unlikely to be confused with other catalog skills."
          },
          "context_keywords": {
            "context_keywords": [
              "OpenTelemetry",
              "Jaeger",
              "Zipkin",
              "tracing spans",
              "context propagation",
              "service mesh",
              "observability",
              "latency analysis",
              "root cause analysis",
              "performance monitoring",
              "distributed systems",
              "microservices",
              "trace visualization",
              "instrumentation",
              "end-to-end tracing"
            ]
          },
          "maturity": {
            "confidence": 0.93,
            "maturity": "well_known",
            "reasoning": "Common in SRE/observability job descriptions and supported by major vendors like Datadog, New Relic, and OpenTelemetry; widely adopted for microservices debugging and performance analysis."
          },
          "skill_id": "distributed-tracing",
          "vendor_license": {
            "confidence": 0.95,
            "license": null,
            "vendor": null,
            "year_introduced": null
          },
          "versioning": {
            "current_version": null,
            "version_aliases": {},
            "versioned": false
          }
        },
        "keep_log": [
          {
            "a_dim_id": "observability-and-operations",
            "a_name": "Observability and Operations",
            "a_role": "__skill_focal__",
            "b_dim_id": "observability-and-incident-triage",
            "b_name": "Observability and Incident Triage",
            "b_role": "DevOps Engineer",
            "pair_kind": "cross_role",
            "reasoning": "Dim A is production observability focused on distributed tracing, span/trace correlation, request propagation, and tools like OpenTelemetry, Jaeger, Zipkin, and Honeycomb. Dim B is DevOps incident triage for failed builds, broken deployments, and unhealthy release environments. Those are different contexts and skills. career-track: no, because a tracing/telemetry specialist is not automatically a build/deployment troubleshooting specialist.",
            "similarity": 0.7415480393828698
          },
          {
            "a_dim_id": "observability-and-operations",
            "a_name": "Observability and Operations",
            "a_role": "__skill_focal__",
            "b_dim_id": "observability-and-operations",
            "b_name": "Observability and Operations",
            "b_role": "Cloud Architect",
            "pair_kind": "cross_role",
            "reasoning": "Same label, different cluster. Dim A is hands-on distributed tracing for production debugging: request propagation, span/trace correlation, OpenTelemetry, Jaeger/Zipkin, Honeycomb, latency analysis. Dim B is cloud-architecture observability readiness: defining telemetry and operational controls workloads must expose. career-track: no, because a tracing/observability engineer is not naturally a cloud architect setting platform supportability requirements.",
            "similarity": 0.7017405935350323
          }
        ],
        "locked_dimensions": [
          {
            "description": "Telemetry, monitoring, logging, and tracing practices used to understand system behavior in production. Distributed Tracing belongs here because it helps correlate requests across services, identify latency bottlenecks, and support incident diagnosis.",
            "exemplar_skills": [
              "Distributed Tracing",
              "OpenTelemetry",
              "Jaeger",
              "Zipkin",
              "Honeycomb tracing",
              "Trace correlation",
              "Span instrumentation"
            ],
            "in_scope": "Distributed Tracing, tracing instrumentation, span and trace correlation, request propagation, service dependency maps, OpenTelemetry, Jaeger, Zipkin, Honeycomb, latency analysis, production debugging",
            "name": "Observability and Operations",
            "out_of_scope": "Application logging formats, log aggregation pipelines, and log search workflows, metrics collection and alert tuning, incident command procedures and escalation runbooks, synthetic monitoring and uptime checks",
            "overlap_flags": [
              {
                "reason": "Tracing is often used during incident triage, but this dimension focuses on the broader observability stack rather than response workflow.",
                "with_dim_id": "observability-and-incident-triage",
                "with_dim_name": null,
                "with_role": "DevOps Engineer"
              }
            ],
            "tentative_id": "observability-and-operations"
          },
          {
            "description": "Instrumentation patterns for emitting telemetry from applications and services. Distributed Tracing fits here because it requires adding spans, context propagation, and trace metadata to code paths so requests can be followed end to end.",
            "exemplar_skills": [
              "Distributed Tracing",
              "Span creation",
              "Trace context propagation",
              "Telemetry instrumentation",
              "Trace IDs",
              "Baggage propagation",
              "Instrumentation libraries"
            ],
            "in_scope": "Distributed Tracing, span creation, trace context propagation, instrumentation libraries, trace IDs, baggage propagation, middleware hooks, SDK-based telemetry, custom span attributes",
            "name": "Service Telemetry Instrumentation",
            "out_of_scope": "Dashboarding and alerting on collected telemetry, log management and log parsing, infrastructure monitoring and host metrics, incident response processes and on-call operations",
            "overlap_flags": [
              {
                "reason": "Telemetry instrumentation feeds observability platforms, but this dimension is specifically about adding tracing hooks in code.",
                "with_dim_id": "observability-and-operations",
                "with_dim_name": null,
                "with_role": "Cloud Architect"
              }
            ],
            "tentative_id": "d_init_01"
          },
          {
            "description": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
            "exemplar_skills": [
              "Observability and Operations"
            ],
            "in_scope": "Skills, tools, and practices that belong under Observability and Operations for the target role, including items implied by the dimension rationale.",
            "name": "Observability and Operations",
            "out_of_scope": "Adjacent clusters explicitly not owned by Observability and Operations, including unrelated platforms, roles, and skill families per library policy.",
            "overlap_flags": [],
            "tentative_id": "observability-and-operations"
          }
        ],
        "merge_log": [],
        "placed": {
          "name": "Distributed Tracing",
          "placement_confidence": 0.92,
          "primary_dimension": "observability-and-operations",
          "reasoning": "Deterministic JD placement: locked_dimensions has 3 dimension(s) from skill-driven dimension generation after reconciliation; primary_dimension is the first locked dim.",
          "secondary_dimensions": [
            "d_init_01"
          ],
          "skill_id": "distributed-tracing"
        },
        "relationships": {
          "child_skills": [],
          "parent_skills": [
            "observability"
          ],
          "related_to": [
            "artifact-logging",
            "crash-analytics",
            "failure-analysis",
            "profiling",
            "context-management",
            "anomaly-detection",
            "data-drift-detection"
          ],
          "requires": [],
          "skill_id": "distributed-tracing",
          "suppress_on_match": []
        },
        "skill_id": "distributed-tracing",
        "split_log": [],
        "typed": {
          "alternatives_considered": [],
          "confidence": 0.95,
          "name": "Distributed Tracing",
          "reasoning": "Distributed Tracing is fundamentally a knowledge unit about tracing requests across services, so by the Concept vs Methodology rule it is a Concept rather than a tool or architecture.",
          "skill_id": "distributed-tracing",
          "subtype": "observability_concept",
          "type": "Concept"
        },
        "warnings": [
          "stage3_post_filter_dropped_catalog_only_locked_dims:42-\u003e3"
        ]
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "React Frontend Development",
            "id": 96,
            "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
            "slug": "d_init_01",
            "source": "db"
          },
          "input_skill": "ITAR",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "ITAR",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Standard",
          "skill_nature": "STANDARD",
          "sub_category": "export_control_regulation",
          "typical_lifespan": "EVERGREEN",
          "version_strategy": "NOT_APPLICABLE",
          "volatility": "STABLE"
        },
        "enrichment": {
          "ambiguity": {
            "ambiguity_flag": false,
            "confused_with": [],
            "reasoning": "ITAR is a specific, well-defined export control regulation acronym; unlikely to be confused with other catalog skills."
          },
          "context_keywords": {
            "context_keywords": [
              "compliance",
              "export control",
              "regulatory framework",
              "defense articles",
              "technical data",
              "ITAR registration",
              "government contracts",
              "export licenses",
              "controlled unclassified information",
              "EAR",
              "ITAR exemptions",
              "international traffic",
              "security clearance",
              "foreign military sales",
              "sensitive technology"
            ]
          },
          "maturity": {
            "confidence": 0.91,
            "maturity": "niche",
            "reasoning": "ITAR appears in a limited set of defense/aerospace job postings and compliance roles, not as a general-purpose engineering skill; market demand is concentrated in regulated industries."
          },
          "skill_id": "itar",
          "vendor_license": {
            "confidence": 0.9,
            "license": null,
            "vendor": null,
            "year_introduced": null
          },
          "versioning": {
            "current_version": null,
            "version_aliases": {},
            "versioned": false
          }
        },
        "keep_log": [],
        "locked_dimensions": [
          {
            "description": "Controls and review practices for complying with export control laws and restrictions on technical data, software, and access. ITAR belongs here because it governs whether defense-related information, services, or systems can be shared, accessed, or transferred.",
            "exemplar_skills": [
              "ITAR",
              "EAR",
              "export classification",
              "deemed export review",
              "technology control plans",
              "export licensing"
            ],
            "in_scope": "ITAR, EAR, export classification, controlled technical data, deemed export review, access restrictions, foreign person screening, export licensing, technology control plans",
            "name": "Export Control Compliance",
            "out_of_scope": "AI model governance, privacy retention rules, sanctions screening for payments, general corporate legal review, import customs compliance",
            "overlap_flags": [
              {
                "reason": "Both can involve access controls and compliance review, but ITAR is specifically about export-controlled technical data and transfer restrictions.",
                "with_dim_id": "ai-governance-and-model-security",
                "with_dim_name": null,
                "with_role": "AI Engineer, ML Engineer, ML Ops Engineer"
              },
              {
                "reason": "Identity controls may enforce ITAR restrictions, but the dimension here is the regulatory export-control policy rather than IAM design.",
                "with_dim_id": "identity-and-access-architecture",
                "with_dim_name": null,
                "with_role": "Cloud Architect"
              }
            ],
            "tentative_id": "d_init_01"
          }
        ],
        "merge_log": [],
        "placed": {
          "name": "ITAR",
          "placement_confidence": 0.92,
          "primary_dimension": "d_init_01",
          "reasoning": "Deterministic JD placement: locked_dimensions has 1 dimension(s) from skill-driven dimension generation after reconciliation; primary_dimension is the first locked dim.",
          "secondary_dimensions": [],
          "skill_id": "itar"
        },
        "relationships": {
          "child_skills": [],
          "parent_skills": [],
          "related_to": [
            "model-supply-chain-security",
            "api-security",
            "authentication",
            "sdlc",
            "eu-ai-act-readiness",
            "nist-ai-rmf"
          ],
          "requires": [],
          "skill_id": "itar",
          "suppress_on_match": []
        },
        "skill_id": "itar",
        "split_log": [],
        "typed": {
          "alternatives_considered": [],
          "confidence": 0.97,
          "name": "ITAR",
          "reasoning": "ITAR is a formal U.S. government export-control regulation, so by the Standard rule it is an industry/body-defined specification rather than a methodology or concept.",
          "skill_id": "itar",
          "subtype": "export_control_regulation",
          "type": "Standard"
        },
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "React Frontend Development",
            "id": 96,
            "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
            "slug": "d_init_01",
            "source": "db"
          },
          "input_skill": "EAR",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "EAR",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Standard",
          "skill_nature": "STANDARD",
          "sub_category": "enterprise_architecture_reference",
          "typical_lifespan": "EVERGREEN",
          "version_strategy": "NOT_APPLICABLE",
          "volatility": "STABLE"
        },
        "enrichment": {
          "ambiguity": {
            "ambiguity_flag": true,
            "confused_with": [
              "earl",
              "ear_training"
            ],
            "reasoning": "\u201cEAR\u201d is an acronym used for multiple unrelated concepts (e.g., enterprise architecture reference vs other EAR meanings), so a JD mention could be misread."
          },
          "context_keywords": {
            "context_keywords": [
              "TOGAF",
              "Zachman",
              "architecture framework",
              "business architecture",
              "information systems",
              "enterprise modeling",
              "reference architecture",
              "capability mapping",
              "architecture governance",
              "stakeholder engagement",
              "architecture principles",
              "technology roadmap",
              "solution architecture",
              "business process modeling",
              "system integration"
            ]
          },
          "maturity": {
            "confidence": 0.78,
            "maturity": "niche",
            "reasoning": "EAR (Enterprise Architecture Reference) appears in relatively few job postings compared with mainstream stacks; market demand is mostly in enterprise architecture roles rather than general engineering hiring."
          },
          "skill_id": "ear",
          "vendor_license": {
            "confidence": 0.9,
            "license": null,
            "vendor": null,
            "year_introduced": null
          },
          "versioning": {
            "current_version": null,
            "version_aliases": {},
            "versioned": false
          }
        },
        "keep_log": [],
        "locked_dimensions": [
          {
            "description": "Covers reviewing solution designs against enterprise standards, target-state architecture, and cross-domain constraints. EAR fits here as the common abbreviation for architecture review in platform and engineering organizations.",
            "exemplar_skills": [
              "EAR",
              "architecture review",
              "solution architecture review",
              "design exception review",
              "reference architecture compliance"
            ],
            "in_scope": "EAR, architecture review boards, solution architecture review, target-state alignment, reference architecture compliance, design exception review, platform standards review, cross-domain dependency review",
            "name": "Enterprise Architecture Review",
            "out_of_scope": "implementation coding, infrastructure provisioning, incident triage, model governance, security testing",
            "overlap_flags": [
              {
                "reason": "Architecture reviews often consider operational readiness, monitoring, and supportability requirements.",
                "with_dim_id": "observability-and-operations",
                "with_dim_name": null,
                "with_role": "Cloud Architect"
              },
              {
                "reason": "Enterprise architecture reviews frequently evaluate identity, authorization, and access boundary decisions.",
                "with_dim_id": "identity-and-access-architecture",
                "with_dim_name": null,
                "with_role": "Cloud Architect"
              }
            ],
            "tentative_id": "d_init_01"
          }
        ],
        "merge_log": [],
        "placed": {
          "name": "EAR",
          "placement_confidence": 0.92,
          "primary_dimension": "d_init_01",
          "reasoning": "Deterministic JD placement: locked_dimensions has 1 dimension(s) from skill-driven dimension generation after reconciliation; primary_dimension is the first locked dim.",
          "secondary_dimensions": [],
          "skill_id": "ear"
        },
        "relationships": {
          "child_skills": [],
          "parent_skills": [],
          "related_to": [
            "enterprise-saas",
            "authentication",
            "api",
            "aws",
            "evaluation",
            "elk"
          ],
          "requires": [],
          "skill_id": "ear",
          "suppress_on_match": []
        },
        "skill_id": "ear",
        "split_log": [],
        "typed": {
          "alternatives_considered": [
            "Concept: ruled out \u2014 while it is a knowledge area, the acronym is more commonly used as a formal reference/specification in enterprise architecture contexts.",
            "Architecture: ruled out \u2014 it names a reference/specification about architecture rather than a system-shape pattern itself."
          ],
          "confidence": 0.67,
          "name": "EAR",
          "reasoning": "EAR most plausibly refers to Enterprise Architecture Reference, which is an industry-defined specification rather than a tool, language, or framework, so the Standard rule applies.",
          "skill_id": "ear",
          "subtype": "enterprise_architecture_reference",
          "type": "Standard"
        },
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "React Frontend Development",
            "id": 96,
            "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
            "slug": "d_init_01",
            "source": "db"
          },
          "input_skill": "DFARS",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "DFARS",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Standard",
          "skill_nature": "STANDARD",
          "sub_category": "defense_federal_acquisition_regulation_supplement",
          "typical_lifespan": "EVERGREEN",
          "version_strategy": "NOT_APPLICABLE",
          "volatility": "STABLE"
        },
        "enrichment": {
          "ambiguity": {
            "ambiguity_flag": false,
            "confused_with": [],
            "reasoning": "DFARS is a specific, well-defined defense/federal acquisition regulation acronym; typical JDs won\u2019t confuse it with other similarly named standards."
          },
          "context_keywords": {
            "context_keywords": [
              "compliance",
              "audit",
              "contracting",
              "regulatory",
              "procurement",
              "DFARS clause",
              "risk management",
              "supply chain",
              "government contracts",
              "cost accounting",
              "subcontracting",
              "certification",
              "reporting requirements",
              "defense contracts",
              "contract modifications"
            ]
          },
          "maturity": {
            "confidence": 0.93,
            "maturity": "niche",
            "reasoning": "DFARS appears mainly in U.S. defense procurement and compliance job postings, not general software JDs; market signal is concentrated government-contractor hiring rather than broad tech adoption."
          },
          "skill_id": "dfars",
          "vendor_license": {
            "confidence": 0.9,
            "license": null,
            "vendor": null,
            "year_introduced": null
          },
          "versioning": {
            "current_version": null,
            "version_aliases": {},
            "versioned": false
          }
        },
        "keep_log": [],
        "locked_dimensions": [
          {
            "description": "Compliance with U.S. Department of Defense contracting requirements and procurement clauses. DFARS belongs here because it governs how contractors handle controlled information, cybersecurity obligations, and contract flow-down requirements.",
            "exemplar_skills": [
              "DFARS",
              "DoD contracting compliance",
              "CUI safeguarding",
              "NIST SP 800-171",
              "CMMC",
              "subcontractor flow-down management"
            ],
            "in_scope": "DFARS, DoD contract clauses, flow-down requirements, CMMC alignment, safeguarding controlled unclassified information (CUI), NIST SP 800-171 implementation, subcontractor compliance, defense procurement compliance",
            "name": "Defense Contract Compliance",
            "out_of_scope": "General corporate legal review, export control regimes like ITAR/EAR, privacy laws such as GDPR/CCPA, vendor security questionnaires not tied to defense contracts, broader AI governance policy",
            "overlap_flags": [
              {
                "reason": "DFARS can intersect with AI security and governance when defense contracts impose controls on model data, but the core concept is contract compliance rather than model risk management.",
                "with_dim_id": "ai-governance-and-model-security",
                "with_dim_name": null,
                "with_role": "AI Engineer, ML Engineer, ML Ops Engineer"
              },
              {
                "reason": "DFARS may affect third-party vendor selection and due diligence for defense work, but this dimension is broader procurement/compliance screening.",
                "with_dim_id": "ai-vendor-and-third-party-due-diligence",
                "with_dim_name": null,
                "with_role": "AI Compliance Officer"
              }
            ],
            "tentative_id": "d_init_01"
          }
        ],
        "merge_log": [],
        "placed": {
          "name": "DFARS",
          "placement_confidence": 0.92,
          "primary_dimension": "d_init_01",
          "reasoning": "Deterministic JD placement: locked_dimensions has 1 dimension(s) from skill-driven dimension generation after reconciliation; primary_dimension is the first locked dim.",
          "secondary_dimensions": [],
          "skill_id": "dfars"
        },
        "relationships": {
          "child_skills": [],
          "parent_skills": [],
          "related_to": [
            "nist-ai-rmf",
            "eu-ai-act-readiness",
            "sdlc",
            "model-supply-chain-security",
            "document-processing",
            "failure-analysis",
            "api"
          ],
          "requires": [],
          "skill_id": "dfars",
          "suppress_on_match": []
        },
        "skill_id": "dfars",
        "split_log": [],
        "typed": {
          "alternatives_considered": [],
          "confidence": 0.97,
          "name": "DFARS",
          "reasoning": "DFARS is a formal government-issued procurement regulation, so by the Standard rule it is an industry/body-defined specification rather than a concept or methodology.",
          "skill_id": "dfars",
          "subtype": "defense_federal_acquisition_regulation_supplement",
          "type": "Standard"
        },
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "ARM",
    "EKS",
    "Site Reliability Engineering",
    "Logging",
    "Metrics",
    "Distributed Tracing",
    "ITAR",
    "EAR",
    "DFARS"
  ]
}

{
  "chosen_role": {
    "display_name": "Cloud Architect",
    "id": 9,
    "rationale": "The primary skills heavily focus on cloud technologies which align with a Cloud Architect\u0027s responsibilities.",
    "role_archetype": null,
    "slug": "cloud-architect",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Azure",
      "tag": "in_db"
    },
    {
      "skill": "AWS",
      "tag": "in_db"
    },
    {
      "skill": "Terraform",
      "tag": "in_db"
    },
    {
      "skill": "CloudFormation",
      "tag": "in_db"
    },
    {
      "skill": "ARM",
      "tag": "new"
    },
    {
      "skill": "Bicep",
      "tag": "in_db"
    },
    {
      "skill": "AKS",
      "tag": "in_db"
    },
    {
      "skill": "EKS",
      "tag": "new"
    },
    {
      "skill": "ECS",
      "tag": "in_db"
    },
    {
      "skill": "Relational Databases",
      "tag": "in_db"
    },
    {
      "skill": "CI/CD",
      "tag": "in_db"
    },
    {
      "skill": "DevSecOps",
      "tag": "in_db"
    },
    {
      "skill": "Site Reliability Engineering",
      "tag": "new"
    },
    {
      "skill": "Logging",
      "tag": "new"
    },
    {
      "skill": "Metrics",
      "tag": "new"
    },
    {
      "skill": "Distributed Tracing",
      "tag": "new"
    },
    {
      "skill": "ITAR",
      "tag": "new"
    },
    {
      "skill": "EAR",
      "tag": "new"
    },
    {
      "skill": "DFARS",
      "tag": "new"
    }
  ],
  "persistence": {
    "items": [
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms",
          "id": 20,
          "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
          "slug": "cloud-platforms",
          "source": "db"
        },
        "dimension_id": 20,
        "input_skill": "Azure",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Backend Engineer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Cybersecurity Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          },
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          },
          {
            "display_name": "Full Stack Engineer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "ML Ops Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 188,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms \u0026 Managed Services",
          "id": 221,
          "rationale": "Operates and integrates vendor-specific cloud compute, storage, and hosting services.",
          "slug": "cloud-platforms-managed-services",
          "source": "db"
        },
        "dimension_id": 221,
        "input_skill": "Azure",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Full Stack Engineer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 188,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms for AI Deployment",
          "id": 211,
          "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
          "slug": "cloud-platforms-for-ai-deployment",
          "source": "db"
        },
        "dimension_id": 211,
        "input_skill": "Azure",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AI Engineer",
            "id": 13,
            "rationale": null,
            "role_archetype": null,
            "slug": "ai-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 188,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Provider Platforms",
          "id": 131,
          "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
          "slug": "cloud-provider-platforms",
          "source": "db"
        },
        "dimension_id": 131,
        "input_skill": "Azure",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 188,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Security Posture Tools",
          "id": 64,
          "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
          "slug": "cloud-security-posture-tools",
          "source": "db"
        },
        "dimension_id": 64,
        "input_skill": "Azure",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cybersecurity Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 188,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms",
          "id": 20,
          "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
          "slug": "cloud-platforms",
          "source": "db"
        },
        "dimension_id": 20,
        "input_skill": "AWS",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Backend Engineer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Cybersecurity Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          },
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          },
          {
            "display_name": "Full Stack Engineer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "ML Ops Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms for AI Deployment",
          "id": 211,
          "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
          "slug": "cloud-platforms-for-ai-deployment",
          "source": "db"
        },
        "dimension_id": 211,
        "input_skill": "AWS",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AI Engineer",
            "id": 13,
            "rationale": null,
            "role_archetype": null,
            "slug": "ai-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Provider Platforms",
          "id": 131,
          "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
          "slug": "cloud-provider-platforms",
          "source": "db"
        },
        "dimension_id": 131,
        "input_skill": "AWS",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Security Posture Tools",
          "id": 64,
          "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
          "slug": "cloud-security-posture-tools",
          "source": "db"
        },
        "dimension_id": 64,
        "input_skill": "AWS",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cybersecurity Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Infrastructure as Code",
          "id": 132,
          "rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
          "slug": "infrastructure-as-code",
          "source": "db"
        },
        "dimension_id": 132,
        "input_skill": "Terraform",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 286,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Infrastructure as Code for ML",
          "id": 57,
          "rationale": "Tools for provisioning and managing ML infrastructure resources through code.",
          "slug": "infrastructure-as-code-for-ml",
          "source": "db"
        },
        "dimension_id": 57,
        "input_skill": "Terraform",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 286,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Infrastructure as Code",
          "id": 132,
          "rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
          "slug": "infrastructure-as-code",
          "source": "db"
        },
        "dimension_id": 132,
        "input_skill": "CloudFormation",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 837,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Infrastructure as Code",
          "id": 132,
          "rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
          "slug": "infrastructure-as-code",
          "source": "db"
        },
        "dimension_id": 132,
        "input_skill": "Bicep",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 838,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Container Orchestration Platforms",
          "id": 134,
          "rationale": "Platforms that schedule and manage containerized workloads across clusters and environments. Cloud Architects need these to define workload placement standards, cluster boundaries, and platform capabilities.",
          "slug": "container-orchestration-platforms",
          "source": "db"
        },
        "dimension_id": 134,
        "input_skill": "AKS",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1221,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Container Orchestration Platforms",
          "id": 134,
          "rationale": "Platforms that schedule and manage containerized workloads across clusters and environments. Cloud Architects need these to define workload placement standards, cluster boundaries, and platform capabilities.",
          "slug": "container-orchestration-platforms",
          "source": "db"
        },
        "dimension_id": 134,
        "input_skill": "ECS",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 854,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "Relational Databases",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1345,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD Pipeline Platforms",
          "id": 150,
          "rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
          "slug": "ci-cd-pipeline-platforms",
          "source": "db"
        },
        "dimension_id": 150,
        "input_skill": "CI/CD",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1190,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD for Machine Learning",
          "id": 56,
          "rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
          "slug": "ci-cd-for-machine-learning",
          "source": "db"
        },
        "dimension_id": 56,
        "input_skill": "CI/CD",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1190,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD Pipeline Platforms",
          "id": 150,
          "rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
          "slug": "ci-cd-pipeline-platforms",
          "source": "db"
        },
        "dimension_id": 150,
        "input_skill": "DevSecOps",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Deployment and Release Patterns",
          "id": 140,
          "rationale": "Patterns for promoting changes safely across environments, including rollout, rollback, and release gating strategies. Cloud Architects define these patterns so teams can deploy consistently across the platform.",
          "slug": "deployment-and-release-patterns",
          "source": "db"
        },
        "dimension_id": 140,
        "input_skill": "DevSecOps",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Infrastructure as Code",
          "id": 132,
          "rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
          "slug": "infrastructure-as-code",
          "source": "db"
        },
        "dimension_id": 132,
        "input_skill": "DevSecOps",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "ARM",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "New skill saved \u00b7 Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1621,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Kubernetes for ML Workloads",
          "id": 47,
          "rationale": "Kubernetes-native components used to schedule, accelerate, and isolate ML training and serving workloads. This includes GPU enablement and ML-specific controllers rather than generic cluster administration.",
          "slug": "kubernetes-for-ml-workloads",
          "source": "db"
        },
        "dimension_id": 47,
        "input_skill": "EKS",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "New skill saved \u00b7 Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "ML Ops Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1622,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "Site Reliability Engineering",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "New skill saved \u00b7 Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1623,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Observability and Operations",
          "id": 143,
          "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
          "slug": "observability-and-operations",
          "source": "db"
        },
        "dimension_id": 143,
        "input_skill": "Logging",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "New skill saved \u00b7 Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1624,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Experiment Tracking and Evaluation",
          "id": 44,
          "rationale": "Tools and practices for recording experiments, comparing runs, and assessing model quality before release. This dimension focuses on reproducibility, metrics, artifacts, and offline evaluation workflows.",
          "slug": "experiment-tracking-and-evaluation",
          "source": "db"
        },
        "dimension_id": 44,
        "input_skill": "Metrics",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "New skill saved \u00b7 Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "ML Ops Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1625,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Observability and Operations",
          "id": 143,
          "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
          "slug": "observability-and-operations",
          "source": "db"
        },
        "dimension_id": 143,
        "input_skill": "Metrics",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "New skill saved \u00b7 Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1625,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Observability and Operations",
          "id": 143,
          "rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
          "slug": "observability-and-operations",
          "source": "db"
        },
        "dimension_id": 143,
        "input_skill": "Distributed Tracing",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "New skill saved \u00b7 Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1626,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "Distributed Tracing",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "New skill saved \u00b7 Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1626,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "ITAR",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "New skill saved \u00b7 Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1627,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "EAR",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "New skill saved \u00b7 Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1628,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 9,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "DFARS",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "New skill saved \u00b7 Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1629,
        "skill_tag": "in_db",
        "skipped_reason": null
      }
    ],
    "new_skills_created": 9,
    "role_dimension_saved": 0,
    "skill_dimension_saved": 11,
    "skipped": 3
  },
  "planner_output": null,
  "run_id": "ca344d45-7a3f-4b96-9548-86d8e493d216"
}