Pipeline run
e0f835dd-c75c-4254-9669-3ffd27599b35
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionvocab breakdown (legacy)
Signals
Post-classification
Captured for admin review
Design, implement, and operate scalable services for GPU-based model training, tuning, and inference. Build tools and APIs that enable internal and external users to easily launch, monitor, and manage…
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
AI Infrastructure Engineer
domain · AI / ML CASE DOMAINslug: ai-infrastructure-engineer · id: 155 · source: db
Domain=AI / ML; The JD is centered on building and operating GPU-based AI platform infrastructure, scalable distributed services, and cloud/IaaS systems, which best matches AI Infrastructure Engineer.
Matched skills
Matched dimensions
Matched KRAs
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
Job Description Senior Software Development Engineer - OCI AI Platform, Services & Solutions Org OCI is Oracle’s next-generation cloud platform, built for the most demanding enterprise workloads. We are focused on delivering high-performance computing, storage, networking, and platform services at global scale. The AI Platform, Services & Solutions organization within OCI is building a robust ecosystem to support the end-to-end lifecycle of AI and machine learning workloads. From GPU infrastructure and training pipelines to model serving and deployment tools—we empower teams across Oracle and our customers to build and deploy AI at scale. We are looking for a Senior Software Engineer to join our growing team and help shape the future of AI infrastructure and services at Oracle. You will work on critical components of OCI’s AI platform, including high-scale GPU cluster management, self-service ML infrastructure, and model serving systems. Work on critical AI infrastructure that powers Oracle’s GenAI and ML initiatives. Contribute to high-impact projects with visibility across Oracle Cloud. Collaborate with top engineers and researchers in a fast-paced, innovation-driven environment. Grow your career in a supportive, mission-driven team building the future of enterprise AI. This is a highly technical, hands-on role where you’ll build large-scale distributed systems, optimize AI/ML workflows, and collaborate with cross-functional teams to deliver scalable and reliable solutions. Responsibilities Design, implement, and operate scalable services for GPU-based model training, tuning, and inference. Build tools and APIs that enable internal and external users to easily launch, monitor, and manage ML workloads. Collaborate with product, infrastructure, and ML engineering teams to define and deliver key platform features. Optimize performance, reliability, and efficiency of AI infrastructure using best-in-class engineering practices. Contribute to platform automation, observability, CI/CD pipelines, and operational excellence. Troubleshoot complex issues in distributed systems and participate in on-call rotations as needed. Mentor junior engineers and participate in design and code reviews. What You’ll Do • Build cloud service on top of the modern Infrastructure as a Service (IaaS) building blocks at OCI • Design and build distributed, scalable, fault tolerant software systems • Participate in the entire software lifecycle – development, testing, CI and production operations • Leverage internal tooling at OCI to develop, build, deploy and troubleshoot software • Participate in on-call for the service with the team Qualifications • 4+ years of experience shipping scalable, cloud native distributed systems • Experience building control plane/data plane solutions for cloud native companies • Proficient in Go, Java, Python • Experience with container orchestration like Kubernetes • Experienced at building highly available services, possessing knowledge of common service-oriented design patterns and service-to-service communication protocols • Experience with production operations and best practices for putting quality code in production and troubleshoot issues when they arise • Able to effectively communicate technical ideas verbally and in writing (technical proposals, design specs, architecture diagrams and presentations) • BS in Computer Science, or equivalent experience Preferred Qualifications • MS in Computer Science • Experience in diagnosing, troubleshooting and resolving performance issues in complex environments • Deep understanding of Unix-like operating systems • Production experience with Cloud and ML technologies • Generative AI, LLM, Machine learning experience Qualifications Career Level - IC3 About Us As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s challenges. We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity. We know that true innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing an inclusive workforce that promotes opportunities for all. Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing accommodation-request_mb@oracle.com or by calling +1 888 404 2494 in the United States. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- UNVERSIONED
Aliases — catalog
- CI/CD (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Ci Cd Process
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: CI/CD appears in a large share of software engineering JDs and is a standard requirement across DevOps, platform, and backend roles; major vendors like GitHub, GitLab, and AWS all center product roadmaps on CI/CD pipelines.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 900
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
CI/CD Pipeline Platforms Catalog dimension db id 150
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
CI/CD for Machine Learning Catalog dimension db id 56
Library dimension (catalog)
Roles linked in library: ML Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
CI/CD for Machine Learning
ci-cd-for-machine-learning
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Distributed Systems (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Distributed Systems
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Common hiring requirement in backend/platform JDs at large tech firms; appears across AWS, Kafka, microservices, and systems roles, with strong GitHub/Stack Overflow activity and no sunset signal.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1035
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Platforms Catalog dimension db id 20
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer
-
Performance and Scalability Tuning Catalog dimension db id 11
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Platforms
cloud-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Performance and Scalability Tuning
performance-and-scalability-tuning
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- A/B Testing (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Experiment Design Methodology
- Confidence
- 0.97
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Commonly listed in product, growth, and analytics job descriptions; major platforms like Optimizely and Google Optimize popularized it, and it remains a standard experimentation practice across SaaS and e-commerce.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 1214
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
-
Systems Programming Catalog dimension db id 166
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Systems Programming
d_init_02
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Observability (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Observability
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Observability is broadly listed in SRE/DevOps job descriptions and supported by major vendors like Datadog, Grafana, and New Relic, indicating mainstream hiring demand.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1187
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Observability and Operations Catalog dimension db id 143
Library dimension (catalog)
Roles linked in library: Cloud Architect
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Observability and Operations
observability-and-operations
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
All API 3 persistence rows
Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.
| Skill | Tag | Dimension | Skill↔dim | Role↔dim | Outcome | Notes |
|---|---|---|---|---|---|---|
| CI/CD | in_db |
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| CI/CD | in_db |
CI/CD for Machine Learning
ci-cd-for-machine-learning
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Distributed Systems | in_db |
Cloud Platforms
cloud-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Distributed Systems | in_db |
Performance and Scalability Tuning
performance-and-scalability-tuning
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Distributed Systems | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| A/B Testing | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| A/B Testing | in_db |
Systems Programming
d_init_02
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Observability | in_db |
Observability and Operations
observability-and-operations
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | OCI | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | IaaS | type=Cloud Platforms subtype=general nature=CONCEPT lifespan=EVERGREEN |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
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API 1 — extract-from-jd click to toggle
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"sentence": "Mentor junior engineers and participate in design and code reviews.",
"similarity": 0.4693
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 74,
"score": 0.546,
"slug": "flutter-developer",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "DevOps Engineer",
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"matched_count": 2,
"matched_skills": [
"CI/CD",
"Distributed Systems"
],
"role_id": 10,
"score": 0.5,
"slug": "devops-engineer",
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},
{
"display_name": "ML Engineer",
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"matched_count": 2,
"matched_skills": [
"CI/CD",
"Distributed Systems"
],
"role_id": 3,
"score": 0.5,
"slug": "ml-engineer",
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},
{
"display_name": "Cyber Security Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
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],
"role_id": 5,
"score": 0.25,
"slug": "cybersecurity-engineer",
"total_count": 4
},
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Distributed Systems"
],
"role_id": 2,
"score": 0.25,
"slug": "data-engineer",
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},
{
"display_name": "Backend Developer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Distributed Systems"
],
"role_id": 1,
"score": 0.25,
"slug": "backend-engineer",
"total_count": 4
}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "DOMAIN",
"chosen_role": {
"display_name": "AI Infrastructure Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 155,
"score": 0.97,
"slug": "ai-infrastructure-engineer",
"total_count": null
},
"confidence": 0.97,
"is_new_role": false,
"llm2_fired": false,
"llm2_reasoning": null,
"matched_dimensions": [
"AI platform engineering",
"Cloud infrastructure services",
"Distributed systems reliability",
"Platform automation",
"Operational excellence",
"Performance optimization",
"Software lifecycle ownership",
"Technical mentorship"
],
"matched_kras": [
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"Build tools and APIs for ML workloads",
"Collaborate to define and deliver key platform features",
"Optimize performance, reliability, and efficiency",
"Contribute to platform automation and observability",
"Troubleshoot complex issues in distributed systems",
"Participate in on-call rotations",
"Design and build distributed, scalable, fault tolerant software systems"
],
"matched_skills": [
"GPU-based model training",
"tuning",
"inference",
"APIs",
"distributed systems",
"CI/CD pipelines",
"observability",
"on-call rotations",
"Infrastructure as a Service (IaaS)",
"OCI"
],
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Domain=AI / ML; The JD is centered on building and operating GPU-based AI platform infrastructure, scalable distributed services, and cloud/IaaS systems, which best matches AI Infrastructure Engineer.",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 5,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": {
"best_kra_similarity": 0.0,
"queue_id": 1750,
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"role_slug": "ai-infrastructure-engineer",
"status": "pending"
},
"new_skills_attached": [
{
"is_primary": true,
"queue_id": 22861,
"role_display_name": "AI Infrastructure Engineer",
"role_slug": "ai-infrastructure-engineer",
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},
{
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"role_display_name": "AI Infrastructure Engineer",
"role_slug": "ai-infrastructure-engineer",
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}
],
"queue_entry_id": null,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": null
}
}
API 2 — extract-details
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"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
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"typical_lifespan": "EVERGREEN",
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"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 2028,
"existing_alias_text": "Distributed Systems",
"input_term": "Distributed Systems",
"matched_canonical": {
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"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
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"typical_lifespan": "EVERGREEN",
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},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 2565,
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"is_also_category": false,
"is_extractable": true,
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},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 2527,
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"skill_nature": "CONCEPT",
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{
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{
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},
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},
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]
},
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]
},
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},
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},
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},
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},
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}
],
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],
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},
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},
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},
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],
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},
"input_skill": "Distributed Systems",
"llm_role": null,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Backend Developer",
"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": "Cyber Security 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": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "Java Backend Developer",
"id": 79,
"rationale": null,
"role_archetype": "Engineering",
"slug": "java-backend-developer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Performance and Scalability Tuning",
"id": 11,
"rationale": "Techniques for improving throughput, latency, and resource efficiency in PHP backend services. This includes profiling, query optimization, concurrency limits, memory use, and bottleneck analysis.",
"slug": "performance-and-scalability-tuning",
"source": "db"
},
"input_skill": "Distributed Systems",
"llm_role": null,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
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},
{
"display_name": "Backend Developer",
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"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": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"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 Systems",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "Distributed Systems",
"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": "A/B Testing",
"alias_type": "CANONICAL",
"id": 2565,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 8,
"display_name": "A/B Testing",
"id": 1613,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
"slug": "a-b-testing",
"sub_category_id": 1214,
"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": "A/B Testing",
"llm_role": null,
"roles_from_db": []
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Systems Programming",
"id": 166,
"rationale": "Systems programming covers low-level software development where performance, memory safety, and direct control over resources matter. Rust fits here because it is commonly used for OS-adjacent services, infrastructure components, and other performance-sensitive systems code.",
"slug": "d_init_02",
"source": "db"
},
"input_skill": "A/B Testing",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "A/B Testing",
"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": "Observability",
"alias_type": "CANONICAL",
"id": 2527,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 2,
"display_name": "Observability",
"id": 1581,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "observability",
"sub_category_id": 1187,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Observability and Operations",
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"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": "Observability",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Architect",
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"role_archetype": null,
"slug": "cloud-architect",
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}
]
}
],
"input_skill": "Observability",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"OCI",
"IaaS"
]
}
API 3 — final-role-output
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"display_name": "AI Infrastructure Engineer",
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"rationale": "Domain=AI / ML; The JD is centered on building and operating GPU-based AI platform infrastructure, scalable distributed services, and cloud/IaaS systems, which best matches AI Infrastructure Engineer.",
"role_archetype": null,
"slug": "ai-infrastructure-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "OCI",
"tag": "new"
},
{
"skill": "IaaS",
"tag": "new"
},
{
"skill": "CI/CD",
"tag": "in_db"
},
{
"skill": "Distributed Systems",
"tag": "in_db"
},
{
"skill": "A/B Testing",
"tag": "in_db"
},
{
"skill": "Observability",
"tag": "in_db"
}
],
"llm_cost_api1_usd": null,
"llm_cost_api2_usd": null,
"llm_cost_api3_usd": null,
"llm_cost_total_usd": null,
"persistence": {
"items": [
{
"chosen_role_id": 155,
"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",
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"role_archetype": null,
"slug": "devops-engineer",
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}
],
"skill_dimension_saved": true,
"skill_id": 1190,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 155,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "CI/CD for Machine Learning",
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"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",
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"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",
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"role_archetype": null,
"slug": "ml-engineer",
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}
],
"skill_dimension_saved": true,
"skill_id": 1190,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 155,
"dimension": {
"difficulty_hint": "well_known",
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"rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
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"source": "db"
},
"dimension_id": 20,
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"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
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},
{
"display_name": "Backend Developer",
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"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
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"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
},
{
"display_name": "Data Engineer",
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"slug": "data-engineer",
"source": "db"
},
{
"display_name": "DevOps Engineer",
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},
{
"display_name": "Fullstack Developer",
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},
{
"display_name": "Go Backend Developer",
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"role_archetype": "Engineering",
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},
{
"display_name": "Java Backend Developer",
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"role_archetype": "Engineering",
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},
{
"display_name": "Kotlin Backend Developer",
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"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
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},
{
"display_name": "ML Engineer",
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"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
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"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
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},
{
"display_name": "Node.js Backend Developer",
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},
{
"display_name": "Python Backend Developer",
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"role_archetype": "Engineering",
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},
{
"display_name": "Scala Backend Developer",
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"role_archetype": "Engineering",
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}
],
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},
{
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},
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"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
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"role_archetype": "Engineering",
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},
{
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"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": "Node.js Backend Developer",
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"role_archetype": "Engineering",
"slug": "node-backend-developer",
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},
{
"display_name": "PHP Backend Developer",
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"role_archetype": "Engineering",
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},
{
"display_name": "Python Backend Developer",
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"role_archetype": "Engineering",
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}
],
"skill_dimension_saved": true,
"skill_id": 1369,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 155,
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"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
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"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 Systems",
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"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,
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},
{
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},
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},
{
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},
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"roles_from_db": [],
"skill_dimension_saved": true,
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},
{
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},
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"roles_from_db": [
{
"display_name": "Cloud Architect",
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}
],
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}
],
"new_skills_created": 0,
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"skill_dimension_saved": 0,
"skipped": 0
},
"planner_output": null,
"run_id": "e0f835dd-c75c-4254-9669-3ffd27599b35"
}