Pipeline run
c1e0853b-28ce-4a68-a9e1-236cd5d6ed57
Pipeline LLM cost (USD)
API 1: $0.0027
API 2: $0.0000
API 3: $0.0000
Total: $0.0027
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 regulatory compliance, review model cards/datasheets/impact assessments, coordinate legal submissions, and keep the AI risk register current while training 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 focused on AI and machine-learning most closely aligns with a modern, cloud-native stack where model development, deployment, and scaling are typically built around contemporary AI tooling and infrastructure.
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 (7)
AI
Machine Learning
EU AI Act
AI ethics
regulatory frameworks
model governance
policy writing
Skill cluster (2 dimension groups, role-scoped)
AI Governance and Model Security
Machine Learning
Cross-cutting / unaligned
AI
EU AI Act
AI ethics
regulatory frameworks
model governance
policy writing
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
—
—
Alias
—
—
KRA
cybersecurity-engineer
0.33
Status:
extract_from_jd_done
Created: 2026-05-18T18:24:43.983230Z
Updated: 2026-05-18T18:24:43.983230Z
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)
regulatory frameworks
Primary
No API 2 row (run stopped after API 1 or history missing)
model governance
Primary
No API 2 row (run stopped after API 1 or history missing)
policy writing
Secondary
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": "regulatory frameworks"
},
{
"is_primary": true,
"skill_name": "model governance"
},
{
"is_primary": false,
"skill_name": "policy writing"
}
],
"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": [],
"kra_match_roles": [
{
"display_name": "Cybersecurity Engineer",
"matched_count": null,
"role_id": 5,
"score": 0.3291,
"slug": "cybersecurity-engineer",
"total_count": null
},
{
"display_name": "Cloud Architect",
"matched_count": null,
"role_id": 9,
"score": 0.3218,
"slug": "cloud-architect",
"total_count": null
},
{
"display_name": "ML Engineer",
"matched_count": null,
"role_id": 3,
"score": 0.3214,
"slug": "ml-engineer",
"total_count": null
},
{
"display_name": "DevOps Engineer",
"matched_count": null,
"role_id": 10,
"score": 0.3009,
"slug": "devops-engineer",
"total_count": null
},
{
"display_name": "AR/VR Engineer",
"matched_count": null,
"role_id": 8,
"score": 0.2992,
"slug": "ar-vr-engineer",
"total_count": null
}
],
"skill_match_roles": [],
"stage35_ran": false
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "F",
"chosen_role": {
"display_name": "ML Engineer",
"matched_count": null,
"role_id": 3,
"score": 0.3214,
"slug": "ml-engineer",
"total_count": null
},
"confidence": 0.7,
"llm2_fired": true,
"llm2_reasoning": "The ML engineer role is most aligned with auditing AI/ML systems, reviewing model documentation, and guiding responsible AI practices, unlike the cloud architect or cybersecurity engineer.",
"queued": false,
"reasoning": "LLM2 picked ml-engineer (confidence 0.70)"
},
"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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