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Pipeline run

ae44c236-198e-463a-b141-820623046212

Pipeline LLM cost (USD)
API 1: $0.0074 API 2: $0.0002 API 3: $0.0000 Total: $0.0076

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
Nature of work · AI model evaluation and improvement
Write Python code to train/evaluate AI models, analyze public databases for insights, and review/rank model answers on CS topics with clear written rationales in notebooks.
"Evaluate and rank AI model responses based on user requests across a wide range of CS topics, providing detailed rationales for your decisions."
Tech stack maturity
Mainstream Modern
The profile centers on widely used programming skills like algorithms, data structures, and Python, which aligns best with a mainstream modern technology stack rather than legacy, cloud-native, or bleeding-edge AI-specific tooling.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
1.70 / 5
Title match
Has AI skill
· AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1):
Frameworks (×2):
Models / concepts (×3): AI
Evidence — skills matched in JD (7)
Python Algorithms Data Structures System Design Jupyter Software Quality Assurance Test Planning
Skill cluster (2 dimension groups, role-scoped)
Python Programming
Python
Cross-cutting / unaligned
Algorithms Data Structures System Design Jupyter Software Quality Assurance Test Planning
Show KRA description ↓
• Write effective, high-quality code to train and evaluate AI models. • Use business sense and analytical abilities to glean valuable insights from public databases • Clearly express the reasoning and logic when writing code in Jupyter notebooks or other suitable mediums • Evaluate and rank AI model responses based on user requests across a wide range of CS topics, providing detailed rationales for your decisions. • Help in improving the quality of model resposne • Bachelor’s/Master’s Degree in Engineering, Computer Science (or equivalent experience). • At least 2+ years of experience working with Python and related technologies. • Exceptional critical thinking and problem-solving skills (including, but not limited to, good knowledge of algorithms and data structures, system design, coding practices, etc.). • Proficiency with the language's syntax and conventions • Nice to have some prior Software Quality Assurance and Test Planning experience • Excellent spoken and written English communication skills with the ability to articulate ideas clearly and comprehensively.

Signals

Skill backend-engineer
0.25
Alias backend-engineer
1.00
KRA ai-engineer
0.53

Post-classification

Centroidupdated · n=1
Alias collision log
New-role queue
New skills captured4
New KRA capturedyes

Captured for admin review

Jupyter AI Governance / Ethics Analyst pending
System Design primary AI Governance / Ethics Analyst pending
Software Quality Assurance AI Governance / Ethics Analyst pending
Test Planning AI Governance / Ethics Analyst pending
R&R fragment (sim 0.00) AI Governance / Ethics Analyst pending

• Write effective, high-quality code to train and evaluate AI models. • Use business sense and analytical abilities to glean valuable insights from public databases • Clearly express the reasoning and…

Status: completed Created: 2026-05-27T13:52:29.870411Z Updated: 2026-05-27T13:54:16.789644Z API 3 duration: 19593 ms
Flow Current 3-step pipeline

1 POST /skills/extract-from-jd

2 POST /skills/extract-details

3 POST /skills/final-role-output

Role Chosen role & resolution

AI Governance / Ethics Analyst

domain · AI / ML CASE DOMAIN

slug: ai-governance-ethics-analyst · id: 156 · source: db

Domain=AI / ML; The JD centers on evaluating and ranking AI model responses, improving response quality, and providing rationales, which aligns more with AI QA/safety and governance work than with building model systems.

Matched skills

PythonJupyter notebooksalgorithms and data structuressystem designcoding practicespublic databasessoftware quality assurancetest planningEnglish communication skills

Matched dimensions

AI model evaluation and rankingResponse quality improvementAnalytical reasoning and critical thinkingTechnical writing and explanationSoftware quality assurance

Matched KRAs

Write effective, high-quality code to train and evaluate AI modelsGlean valuable insights from public databasesClearly express the reasoning and logic when writing codeEvaluate and rank AI model responsesProvide detailed rationales for your decisionsHelp in improving the quality of model response

Resolution: in_db — role exists in library; skill↔dim and role↔dim links saved when applicable.

0
New skills
0
Skill↔dim saved
0
Role↔dim saved
0
Skipped

Job description

We are actively seeking talented Senior Python Developers to join our ambitious team dedicated to pushing the frontiers of AI technology. This opportunity is tailored for professionals who thrive on developing innovative solutions and who aspire to be at the forefront of AI advancements. You will work with different companies in the US who are looking to develop both commercial and research AI solutions.

Job Responsibilities

• Write effective, high-quality code to train and evaluate AI models.
• Use business sense and analytical abilities to glean valuable insights from public databases
• Clearly express the reasoning and logic when writing code in Jupyter notebooks or other suitable mediums
• Evaluate and rank AI model responses based on user requests across a wide range of CS topics, providing detailed rationales for your decisions.
• Help in improving the quality of model resposne


Requirements

• Bachelor’s/Master’s Degree in Engineering, Computer Science (or equivalent experience).
• At least 2+ years of experience working with Python and related technologies.
• Exceptional critical thinking and problem-solving skills (including, but not limited to, good knowledge of algorithms and data structures, system design, coding practices, etc.).
• Proficiency with the language's syntax and conventions
• Nice to have some prior Software Quality Assurance and Test Planning experience
• Excellent spoken and written English communication skills with the ability to articulate ideas clearly and comprehensively.


Offer Details

• Long-term contractor position (no medical/paid leave)
• Full-time dedication (40 hours/week)
• REQUIRED: 5-hour overlap with PST (Pacific Standard Time)


This is a long-term (1y+, no end in sight) offer from our client on a full-time basis. The team is built and managed internally, so if and when this project ends, you will most likely be immediately assigned to another similar project with another client.

Skills from this JD

Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.

Python Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Python id=5 · python

Aliases — catalog

  • Python (CANONICAL) primary
  • Python 2 (VERSION)
  • Python 2.x (VERSION)
  • Python 3 (VERSION)
  • Python 3.10 (VERSION)
  • Python 3.11 (VERSION)
  • Python 3.12 (VERSION)
  • Python 3.x (VERSION)
  • py (VERSION)
  • py2 (VERSION)
  • py3 (VERSION)
  • python 3 (VERSION)
  • python 3.x (VERSION)
  • python2 (VERSION)
  • python3 (VERSION)
  • python3.x (VERSION)

Context tags (catalog)

API Django FastAPI Flask Jupyter NumPy PEP 8 Pandas REST SQLAlchemy asyncio pandas pip pytest type hints venv virtualenv

Stored enrichment (catalog DB)

Category
Language
Sub-category
Programming Language
Vendor
PSF
License
mit
Year introduced
1991
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
3

Maturity reasoning: Python appears in a very high volume of job descriptions across data, backend, automation, and ML roles, and remains a default hiring-pipeline language on major job boards and tech stacks.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
96
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Security Scripting & DSL Languages Catalog dimension db id 248

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer

  • Programming Languages and Scripting Catalog dimension db id 59

    Library dimension (catalog)

    Roles linked in library: Cyber Security Engineer

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

  • Programming Languages for XR Catalog dimension db id 97

    Library dimension (catalog)

    Roles linked in library: AR/VR Engineer

  • Python Programming Catalog dimension db id 290

    Library dimension (catalog)

    Roles linked in library: Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Jupyter Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Algorithms Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Algorithms id=1004 · algorithms

Aliases — catalog

  • Algorithms (CANONICAL)

Context tags (catalog)

Big O notation backtracking binary trees breadth-first search complexity analysis data structures depth-first search divide and conquer dynamic programming graph algorithms greedy algorithms hashing recursion search algorithms sorting algorithms

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Algorithms
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Algorithms are a core hiring staple in software JDs and interview loops across FAANG and general SWE roles; they remain a standard CS curriculum topic rather than a niche tool or sunset technology.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
732
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    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)
Data Structures Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Data Structures id=1003 · data-structures

Aliases — catalog

  • Data Structures (CANONICAL)

Context tags (catalog)

Big O notation arrays binary search complexity analysis dynamic programming graphs hash tables linked lists memory management queues recursion searching algorithms sorting algorithms stacks trees

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Data Structures
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Core CS concept in nearly all software engineering JDs and interview loops; widely taught and expected across roles, with no sunset or replacement signal.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
731
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    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)
System Design Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Conceptual Frameworks
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Software Quality Assurance Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Practices
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Test Planning Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Practices
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED

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
Python in_db
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Algorithms in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Data Structures in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Jupyter | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed System Design | type=Conceptual Frameworks subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Software Quality Assurance | type=Practices subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Test Planning | type=Practices subtype=general nature=PRACTICE lifespan=MULTI_YEAR
nano JD Parser — gpt-4.1-nano click to toggle
RoleSenior Python Developer
ExperienceAt least 2+ years of experience working with Python and related technologies.
DomainSoftware & SaaS Products
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": null,
  "certifications": [],
  "company_name": null,
  "ctc": null,
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        "SaaS",
        "Product Companies"
      ],
      "domain": "Software \u0026 SaaS Products"
    },
    "secondary": null
  },
  "education": [
    {
      "level": "Bachelor\u0027s",
      "qualification": "BTECH/BE/BSC/MTECH/ME/MSC - Engineering / Computer Science (or equivalent)",
      "raw": "Bachelor\u2019s/Master\u2019s Degree in Engineering, Computer Science (or equivalent experience).",
      "requirement": "required"
    }
  ],
  "experience": {
    "max": null,
    "min": 2,
    "raw": "At least 2+ years of experience working with Python and related technologies."
  },
  "job_locations": [],
  "role": "Senior Python Developer",
  "role_aliases": [
    "Python Developer",
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  "role_archetype": "Engineering",
  "roles_and_responsibilities": [
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      "bullet_count": 5,
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      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Write effective, high-quality code",
        "last_5_words": "quality of model resposne"
      },
      "text": "\u2022 Write effective, high-quality code to train and evaluate AI models.\n\u2022 Use business sense and analytical abilities to glean valuable insights from public databases\n\u2022 Clearly express the reasoning and logic when writing code in Jupyter notebooks or other suitable mediums\n\u2022 Evaluate and rank AI model responses based on user requests across a wide range of CS topics, providing detailed rationales for your decisions.\n\u2022 Help in improving the quality of model resposne",
      "word_count": 66
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    {
      "bullet_count": 6,
      "heading": "Requirements",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Bachelor\u2019s/Master\u2019s Degree in Engineering",
        "last_5_words": "articulate ideas clearly and comprehensively."
      },
      "text": "\u2022 Bachelor\u2019s/Master\u2019s Degree in Engineering, Computer Science (or equivalent experience).\n\u2022 At least 2+ years of experience working with Python and related technologies.\n\u2022 Exceptional critical thinking and problem-solving skills (including, but not limited to, good knowledge of algorithms and data structures, system design, coding practices, etc.).\n\u2022 Proficiency with the language\u0027s syntax and conventions\n\u2022 Nice to have some prior Software Quality Assurance and Test Planning experience\n\u2022 Excellent spoken and written English communication skills with the ability to articulate ideas clearly and comprehensively.",
      "word_count": 83
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Python"
    },
    {
      "is_primary": false,
      "skill_name": "Jupyter"
    },
    {
      "is_primary": true,
      "skill_name": "Algorithms"
    },
    {
      "is_primary": true,
      "skill_name": "Data Structures"
    },
    {
      "is_primary": true,
      "skill_name": "System Design"
    },
    {
      "is_primary": false,
      "skill_name": "Software Quality Assurance"
    },
    {
      "is_primary": false,
      "skill_name": "Test Planning"
    }
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  "nano_parsed": {
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  "rejected": false,
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  "stage3_signals": {
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    "alias_match_roles": [
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        "display_name": "Backend Developer",
        "kra_matches": null,
        "matched_count": null,
        "matched_skills": null,
        "role_id": 1,
        "score": 1.0,
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    "kra_match_roles": [
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        "display_name": "AI Engineer",
        "kra_matches": [
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            "kra_text": "Defines evaluation frameworks, automated test suites, and human feedback loops to measure AI feature quality, accuracy, and consistency.",
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            "similarity": 0.5999
          },
          {
            "kra_text": "Defines evaluation frameworks, automated test suites, and human feedback loops to measure AI feature quality, accuracy, and consistency.",
            "sentence": "Evaluate and rank AI model responses based on user requests across a wide range of CS topics, providing detailed rationales for your decisions.",
            "similarity": 0.545
          },
          {
            "kra_text": "Optimizes AI pipeline efficiency by tuning model selection, context window usage, prompt caching, and batching strategies to reduce cost and latency.",
            "sentence": "Help in improving the quality of model resposne",
            "similarity": 0.4497
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 13,
        "score": 0.5315,
        "slug": "ai-engineer",
        "total_count": null
      },
      {
        "display_name": "AI Compliance Officer",
        "kra_matches": [
          {
            "kra_text": "Evaluates AI models for bias in protected attributes, explainability limitations, and transparency requirements in automated decision-making contexts.",
            "sentence": "Evaluate and rank AI model responses based on user requests across a wide range of CS topics, providing detailed rationales for your decisions.",
            "similarity": 0.5737
          },
          {
            "kra_text": "Evaluates AI models for bias in protected attributes, explainability limitations, and transparency requirements in automated decision-making contexts.",
            "sentence": "Write effective, high-quality code to train and evaluate AI models.",
            "similarity": 0.4902
          },
          {
            "kra_text": "Maps AI system behaviors and data processing activities to regulatory requirements including EU AI Act, GDPR, CCPA, and sector-specific compliance frameworks.",
            "sentence": "Use business sense and analytical abilities to glean valuable insights from public databases",
            "similarity": 0.331
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 12,
        "score": 0.465,
        "slug": "ai-compliance-officer",
        "total_count": null
      },
      {
        "display_name": "ML Engineer",
        "kra_matches": [
          {
            "kra_text": "Builds model serving infrastructure to deploy trained models as real-time prediction APIs or batch inference jobs using TorchServe, TensorFlow Serving, or SageMaker.",
            "sentence": "Write effective, high-quality code to train and evaluate AI models.",
            "similarity": 0.5031
          },
          {
            "kra_text": "Evaluates model quality using offline metrics like precision, recall, F1, AUC-ROC, and NDCG, comparing against baselines and business acceptance thresholds.",
            "sentence": "Evaluate and rank AI model responses based on user requests across a wide range of CS topics, providing detailed rationales for your decisions.",
            "similarity": 0.4368
          },
          {
            "kra_text": "Evaluates model quality using offline metrics like precision, recall, F1, AUC-ROC, and NDCG, comparing against baselines and business acceptance thresholds.",
            "sentence": "Help in improving the quality of model resposne",
            "similarity": 0.4034
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 3,
        "score": 0.4478,
        "slug": "ml-engineer",
        "total_count": null
      },
      {
        "display_name": "MLOps Engineer",
        "kra_matches": [
          {
            "kra_text": "Automates ML platform operations including scheduled retraining triggers, pipeline orchestration, evaluation workflows, and alerting configuration.",
            "sentence": "Write effective, high-quality code to train and evaluate AI models.",
            "similarity": 0.4207
          },
          {
            "kra_text": "Supports ML platform incidents by diagnosing model serving failures, feature store pipeline breaks, and training environment configuration issues.",
            "sentence": "Evaluate and rank AI model responses based on user requests across a wide range of CS topics, providing detailed rationales for your decisions.",
            "similarity": 0.4181
          },
          {
            "kra_text": "Validates model performance benchmarks, data schema contracts, and system integration health before signing off on production release readiness.",
            "sentence": "Nice to have some prior Software Quality Assurance and Test Planning experience",
            "similarity": 0.3813
          }
        ],
        "matched_count": null,
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      },
      {
        "display_name": "Angular Frontend Developer",
        "kra_matches": [
          {
            "kra_text": "collaboration with design and QA",
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          },
          {
            "kra_text": "code review and refactoring",
            "sentence": "Clearly express the reasoning and logic when writing code in Jupyter notebooks or other suitable mediums",
            "similarity": 0.3932
          },
          {
            "kra_text": "code review and refactoring",
            "sentence": "Write effective, high-quality code to train and evaluate AI models.",
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    ],
    "skill_match_roles": [
      {
        "display_name": "Backend Developer",
        "kra_matches": null,
        "matched_count": 1,
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          "Python"
        ],
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      {
        "display_name": "Data Engineer",
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      {
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    ]
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "DOMAIN",
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    "confidence": 0.86,
    "is_new_role": false,
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      "AI model evaluation and ranking",
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      "Technical writing and explanation",
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      "Clearly express the reasoning and logic when writing code",
      "Evaluate and rank AI model responses",
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    "matched_skills": [
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      "Jupyter notebooks",
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      "software quality assurance",
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      "English communication skills"
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    "new_role_display_name": null,
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    "queued": false,
    "reasoning": "Domain=AI / ML; The JD centers on evaluating and ranking AI model responses, improving response quality, and providing rationales, which aligns more with AI QA/safety and governance work than with building model systems.",
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  "stage5_updates": {
    "centroid_n_after": 1,
    "centroid_updated": true,
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      "role_slug": "ai-governance-ethics-analyst",
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    "new_skills_attached": [
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    "v3_run_id": null
  }
}
API 2 — extract-details
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      "matched_via": "alias"
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      "matched_via": "alias"
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      "matched_via": "alias"
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            "id": 21,
            "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
            "slug": "programming-languages-for-data-work",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages for ML Systems",
            "id": 39,
            "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
            "slug": "programming-languages-for-ml-systems",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_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"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages for XR",
            "id": 97,
            "rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
            "slug": "programming-languages-for-xr",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "AR/VR Engineer",
              "id": 8,
              "rationale": null,
              "role_archetype": null,
              "slug": "ar-vr-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Python Programming",
            "id": 290,
            "rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
            "slug": "python-programming",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Python Backend Developer",
              "id": 80,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "python-backend-developer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Python",
      "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": [],
      "input_skill": "Jupyter",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "jupyter",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Algorithms",
          "alias_type": "CANONICAL",
          "id": 1615,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 2,
        "display_name": "Algorithms",
        "id": 1004,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "algorithms",
        "sub_category_id": 732,
        "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": "Algorithms",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "Algorithms",
      "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": "Data Structures",
          "alias_type": "CANONICAL",
          "id": 1614,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 2,
        "display_name": "Data Structures",
        "id": 1003,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "data-structures",
        "sub_category_id": 731,
        "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": "Data Structures",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "Data Structures",
      "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": [],
      "input_skill": "System Design",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Conceptual Frameworks",
          "skill_nature": "CONCEPT",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "system-design",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Software Quality Assurance",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Practices",
          "skill_nature": "PRACTICE",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "software-quality-assurance",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Test Planning",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Practices",
          "skill_nature": "PRACTICE",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "test-planning",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Jupyter",
    "System Design",
    "Software Quality Assurance",
    "Test Planning"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "AI Governance / Ethics Analyst",
    "id": 156,
    "rationale": "Domain=AI / ML; The JD centers on evaluating and ranking AI model responses, improving response quality, and providing rationales, which aligns more with AI QA/safety and governance work than with building model systems.",
    "role_archetype": null,
    "slug": "ai-governance-ethics-analyst",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "Jupyter",
      "tag": "new"
    },
    {
      "skill": "Algorithms",
      "tag": "in_db"
    },
    {
      "skill": "Data Structures",
      "tag": "in_db"
    },
    {
      "skill": "System Design",
      "tag": "new"
    },
    {
      "skill": "Software Quality Assurance",
      "tag": "new"
    },
    {
      "skill": "Test Planning",
      "tag": "new"
    }
  ],
  "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": 156,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Security Scripting \u0026 DSL Languages",
          "id": 248,
          "rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
          "slug": "cloud-security-scripting-dsl-languages",
          "source": "db"
        },
        "dimension_id": 248,
        "input_skill": "Python",
        "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": "Cloud Security Engineer",
            "id": 23,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 156,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages",
          "id": 1,
          "rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
          "slug": "programming-languages",
          "source": "db"
        },
        "dimension_id": 1,
        "input_skill": "Python",
        "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 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": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 156,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages and Scripting",
          "id": 59,
          "rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
          "slug": "programming-languages-and-scripting",
          "source": "db"
        },
        "dimension_id": 59,
        "input_skill": "Python",
        "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": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 156,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for Data Work",
          "id": 21,
          "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
          "slug": "programming-languages-for-data-work",
          "source": "db"
        },
        "dimension_id": 21,
        "input_skill": "Python",
        "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": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 156,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for ML Systems",
          "id": 39,
          "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
          "slug": "programming-languages-for-ml-systems",
          "source": "db"
        },
        "dimension_id": 39,
        "input_skill": "Python",
        "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"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 156,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for XR",
          "id": 97,
          "rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
          "slug": "programming-languages-for-xr",
          "source": "db"
        },
        "dimension_id": 97,
        "input_skill": "Python",
        "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": "AR/VR Engineer",
            "id": 8,
            "rationale": null,
            "role_archetype": null,
            "slug": "ar-vr-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 156,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Python Programming",
          "id": 290,
          "rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
          "slug": "python-programming",
          "source": "db"
        },
        "dimension_id": 290,
        "input_skill": "Python",
        "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": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 156,
        "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": "Algorithms",
        "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": 1004,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 156,
        "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": "Data Structures",
        "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": 1003,
        "skill_tag": "in_db",
        "skipped_reason": null
      }
    ],
    "new_skills_created": 0,
    "role_dimension_saved": 0,
    "skill_dimension_saved": 0,
    "skipped": 0
  },
  "planner_output": null,
  "run_id": "ae44c236-198e-463a-b141-820623046212"
}

LLM Calls

Every model call made for this run, in pipeline order. Click a card to see the model's response.

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