Pipeline run

cfd0bb07-cb89-4883-badf-435f5eae28cc

Pipeline LLM cost (USD)

API 1: $0.0028 API 2: $0.0000 API 3: $0.0000 Total: $0.0028

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description

SPARSE JD sources · ai_index: jd · nature_of_work: jd · tech_stack_maturity: jd

Nature of work · AI ethics, regulatory frameworks, model governance, policy writing

Audit AI/ML systems for EU AI Act and US regulatory compliance, review model cards/datasheets/impact assessments, coordinate legal submissions, maintain the AI risk register, and train product teams on responsible-AI practices.

"Audit AI/ML systems for compliance with EU AI Act and emerging US regulations"

Tech stack maturity

Modern Cloud Native

An ML Engineer working with AI, machine learning, and model cards aligns with contemporary AI/ML practices typically found in modern cloud-native technology stacks.

AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)

3.20 / 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, ML, AI/ML, Machine Learning

Evidence — skills matched in JD (10)

AI Machine Learning EU AI Act AI ethics model cards datasheets impact assessments AI risk register responsible-AI principles regulatory frameworks

Skill cluster (2 dimension groups, role-scoped)

AI Governance and Model Security

Machine Learning model cards

Cross-cutting / unaligned

AI EU AI Act AI ethics datasheets impact assessments AI risk register responsible-AI principles regulatory frameworks

Show KRA description ↓

Audit AI/ML systems for compliance with EU AI Act and emerging US regulations Review model cards, datasheets, and impact assessments Coordinate with legal counsel on regulatory submissions Maintain the corporate AI risk register Train product teams on responsible-AI principles AI ethics, regulatory frameworks, model governance, policy writing

Signals

Skill ml-engineer

0.10

Alias ai-compliance-officer

1.00

KRA cybersecurity-engineer

0.42

Status: extract_from_jd_done Created: 2026-05-18T20:34:25.082359Z Updated: 2026-05-18T20:34:25.082359Z

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

No chosen role stored for this run.

Job description

AI Compliance Officer — RegulatoryCo

We're hiring an AI Compliance Officer.

Responsibilities:
- Audit AI/ML systems for compliance with EU AI Act and emerging US regulations
- Review model cards, datasheets, and impact assessments
- Coordinate with legal counsel on regulatory submissions
- Maintain the corporate AI risk register
- Train product teams on responsible-AI principles

Required skills: AI ethics, regulatory frameworks, model governance, policy writing

Skills from this JD

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

AI Primary No API 2 row (run stopped after API 1 or history missing)

Machine Learning Primary No API 2 row (run stopped after API 1 or history missing)

EU AI Act Primary No API 2 row (run stopped after API 1 or history missing)

AI ethics Primary No API 2 row (run stopped after API 1 or history missing)

model cards Primary No API 2 row (run stopped after API 1 or history missing)

datasheets Primary No API 2 row (run stopped after API 1 or history missing)

impact assessments Primary No API 2 row (run stopped after API 1 or history missing)

AI risk register Primary No API 2 row (run stopped after API 1 or history missing)

responsible-AI principles Primary No API 2 row (run stopped after API 1 or history missing)

regulatory frameworks Primary No API 2 row (run stopped after API 1 or history missing)

Library artifacts (this run)

No artifact rows for this run.

nano JD Parser — gpt-4.1-nano click to toggle

RoleAI Compliance Officer

CompanyRegulatoryCo

DomainOther

JD type pass

Show raw JSON

{
  "JD_type": "pass",
  "about_company": null,
  "certifications": [],
  "company_name": "RegulatoryCo",
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [],
      "domain": "Other"
    },
    "secondary": null
  },
  "education": [],
  "experience": {
    "max": null,
    "min": null,
    "raw": null
  },
  "job_locations": [],
  "role": "AI Compliance Officer",
  "role_archetype": "Other",
  "roles_and_responsibilities": [
    {
      "bullet_count": 5,
      "heading": "Responsibilities",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Audit AI/ML systems for compliance",
        "last_5_words": "on responsible-AI principles"
      },
      "text": "Audit AI/ML systems for compliance with EU AI Act and emerging US regulations\nReview model cards, datasheets, and impact assessments\nCoordinate with legal counsel on regulatory submissions\nMaintain the corporate AI risk register\nTrain product teams on responsible-AI principles",
      "word_count": 41
    },
    {
      "bullet_count": 0,
      "heading": "Required skills",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "AI ethics, regulatory frameworks, model",
        "last_5_words": "governance, policy writing"
      },
      "text": "AI ethics, regulatory frameworks, model governance, policy writing",
      "word_count": 8
    }
  ],
  "urls": []
}

API 1 — extract-from-jd click to toggle

{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "AI"
    },
    {
      "is_primary": true,
      "skill_name": "Machine Learning"
    },
    {
      "is_primary": true,
      "skill_name": "EU AI Act"
    },
    {
      "is_primary": true,
      "skill_name": "AI ethics"
    },
    {
      "is_primary": true,
      "skill_name": "model cards"
    },
    {
      "is_primary": true,
      "skill_name": "datasheets"
    },
    {
      "is_primary": true,
      "skill_name": "impact assessments"
    },
    {
      "is_primary": true,
      "skill_name": "AI risk register"
    },
    {
      "is_primary": true,
      "skill_name": "responsible-AI principles"
    },
    {
      "is_primary": true,
      "skill_name": "regulatory frameworks"
    }
  ],
  "jd_role": {
    "display_name": "AI Compliance Officer",
    "rationale": null,
    "role_archetype": "Other",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": null,
    "certifications": [],
    "company_name": "RegulatoryCo",
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [],
        "domain": "Other"
      },
      "secondary": null
    },
    "education": [],
    "experience": {
      "max": null,
      "min": null,
      "raw": null
    },
    "job_locations": [],
    "role": "AI Compliance Officer",
    "role_archetype": "Other",
    "roles_and_responsibilities": [
      {
        "bullet_count": 5,
        "heading": "Responsibilities",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "Audit AI/ML systems for compliance",
          "last_5_words": "on responsible-AI principles"
        },
        "text": "Audit AI/ML systems for compliance with EU AI Act and emerging US regulations\nReview model cards, datasheets, and impact assessments\nCoordinate with legal counsel on regulatory submissions\nMaintain the corporate AI risk register\nTrain product teams on responsible-AI principles",
        "word_count": 41
      },
      {
        "bullet_count": 0,
        "heading": "Required skills",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "AI ethics, regulatory frameworks, model",
          "last_5_words": "governance, policy writing"
        },
        "text": "AI ethics, regulatory frameworks, model governance, policy writing",
        "word_count": 8
      }
    ],
    "urls": []
  },
  "run_id": null,
  "stage3_signals": {
    "alias_match_roles": [
      {
        "display_name": "AI Compliance Officer",
        "matched_count": null,
        "role_id": 12,
        "score": 1.0,
        "slug": "ai-compliance-officer",
        "total_count": null
      }
    ],
    "kra_match_roles": [
      {
        "display_name": "Cybersecurity Engineer",
        "matched_count": null,
        "role_id": 5,
        "score": 0.4176,
        "slug": "cybersecurity-engineer",
        "total_count": null
      },
      {
        "display_name": "ML Engineer",
        "matched_count": null,
        "role_id": 3,
        "score": 0.4149,
        "slug": "ml-engineer",
        "total_count": null
      },
      {
        "display_name": "Cloud Architect",
        "matched_count": null,
        "role_id": 9,
        "score": 0.3819,
        "slug": "cloud-architect",
        "total_count": null
      },
      {
        "display_name": "Data Engineer",
        "matched_count": null,
        "role_id": 2,
        "score": 0.365,
        "slug": "data-engineer",
        "total_count": null
      },
      {
        "display_name": "Backend Engineer",
        "matched_count": null,
        "role_id": 1,
        "score": 0.3591,
        "slug": "backend-engineer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "ML Engineer",
        "matched_count": 1,
        "role_id": 3,
        "score": 0.1,
        "slug": "ml-engineer",
        "total_count": 10
      }
    ],
    "stage35_ran": false
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "F",
    "chosen_role": {
      "display_name": "ML Engineer",
      "matched_count": null,
      "role_id": 3,
      "score": 0.4149,
      "slug": "ml-engineer",
      "total_count": null
    },
    "confidence": 0.85,
    "llm2_fired": true,
    "llm2_reasoning": "The ML Engineer role is more aligned with reviewing model documentation, coordinating on regulatory compliance, and training teams on responsible AI principles than a Cybersecurity Engineer.",
    "queued": false,
    "reasoning": "LLM2 picked ml-engineer (confidence 0.85)"
  },
  "stage5_updates": null
}

API 2 — extract-details

{}

API 3 — final-role-output

{}

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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