Pipeline run
cfa4106d-4dd9-4101-b2db-9a97bdf6a434
Pipeline LLM cost (USD)
API 1: $0.0029
API 2: $0.0000
API 3: $0.0000
Total: $0.0029
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionNature of work
· Field Research / Ethnography
Conduct ethnographic fieldwork aboard research vessels observing AUV deployments, interviewing marine/shipboard teams, and coding notes to study human-AI decision-making and collaboration; then write and present interdisciplinary papers on those findings.
"Conduct ethnographic field studies aboard research vessels tracking AUV (autonomous underwater vehicle) deployments"
Tech stack maturity
Mainstream Modern
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
Evidence — skills matched in JD (5)
AUV
NVivo
Atlas.ti
AI ethics
STS
Skill cluster (1 dimension groups, role-scoped)
Cross-cutting / unaligned
AUV
NVivo
Atlas.ti
AI ethics
STS
Show KRA description ↓
- Conduct ethnographic field studies aboard research vessels tracking AUV (autonomous underwater vehicle) deployments
- Interview marine biologists, AI ethicists, and shipboard crew about deep-sea autonomous decision-making protocols
- Observe and document human-AI collaboration patterns between AUV operators and onboard scientific staff
- Author qualitative research papers on the social dynamics of remote-monitored marine AI systems
- Contribute to interdisciplinary publications across anthropology, marine biology, and AI ethics journals
- Present research at conferences on STS (Science and Technology Studies), oceanography, and AI policy
- PhD or equivalent in cultural anthropology, STS, or qualitative sociology
- 5+ years of ethnographic field experience preferably in scientific or industrial settings
- Comfortable spending 4-6 weeks per year on research vessels in remote Pacific locations
- Strong qualitative coding skills (NVivo, Atlas.ti)
- Familiarity with AI ethics frameworks and STS methodology
Signals
Skill
—
—
Alias
—
—
KRA
ai-compliance-officer
0.49
Post-classification
Centroidupdated · n=6
Alias collision log—
New-role queue—
New skills captured5
New KRA captured—
Captured for admin review
AUV
primary
↔
AI Compliance Officer
pending
NVivo
primary
↔
AI Compliance Officer
pending
Atlas.ti
primary
↔
AI Compliance Officer
pending
AI ethics
primary
↔
AI Compliance Officer
pending
STS
primary
↔
AI Compliance Officer
pending
Status:
extract_from_jd_done
Created: 2026-05-21T17:44:12.541535Z
Updated: 2026-05-21T17:44:13.363126Z
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
Job Title: Underwater Robotics Ethnographer Company: PacificAI Research Institute Location: La Jolla, California, USA Experience: 5+ years field research About the Role: PacificAI Research Institute is hiring an Underwater Robotics Ethnographer to conduct qualitative field studies of autonomous underwater AI robotics deployments in Pacific coral reef ecosystems. You will join a multidisciplinary research team of marine biologists, AI ethicists, and oceanographers. Key Responsibilities: - Conduct ethnographic field studies aboard research vessels tracking AUV (autonomous underwater vehicle) deployments - Interview marine biologists, AI ethicists, and shipboard crew about deep-sea autonomous decision-making protocols - Observe and document human-AI collaboration patterns between AUV operators and onboard scientific staff - Author qualitative research papers on the social dynamics of remote-monitored marine AI systems - Contribute to interdisciplinary publications across anthropology, marine biology, and AI ethics journals - Present research at conferences on STS (Science and Technology Studies), oceanography, and AI policy Required Qualifications: - PhD or equivalent in cultural anthropology, STS, or qualitative sociology - 5+ years of ethnographic field experience preferably in scientific or industrial settings - Comfortable spending 4-6 weeks per year on research vessels in remote Pacific locations - Strong qualitative coding skills (NVivo, Atlas.ti) - Familiarity with AI ethics frameworks and STS methodology
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
AUV
Primary
No API 2 row (run stopped after API 1 or history missing)
NVivo
Primary
No API 2 row (run stopped after API 1 or history missing)
Atlas.ti
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)
STS
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
RoleUnderwater Robotics Ethnographer
CompanyPacificAI Research Institute
Experience5+ years field research
DomainResearch
Location
La Jolla, USA
JD type
pass
Show raw JSON
{
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"about_company": null,
"certifications": [],
"company_name": "PacificAI Research Institute",
"ctc": null,
"domain": {
"primary": {
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"Field Research",
"Ethnographic Research"
],
"domain": "Research"
},
"secondary": null
},
"education": [
{
"level": "Doctorate",
"qualification": "PhD - Cultural Anthropology",
"raw": "PhD or equivalent in cultural anthropology, STS, or qualitative sociology",
"requirement": "required"
}
],
"experience": {
"max": null,
"min": 5,
"raw": "5+ years field research"
},
"job_locations": [
{
"aliases": [
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],
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"country": "USA",
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"work_mode": null
}
],
"role": "Underwater Robotics Ethnographer",
"role_aliases": [
"Ethnographer",
"Field Researcher",
"Cultural Anthropologist"
],
"role_archetype": "Research",
"roles_and_responsibilities": [
{
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"heading_was_present": true,
"source_marker": {
"first_5_words": "Key Responsibilities:",
"last_5_words": "oceanography, and AI policy"
},
"text": "- Conduct ethnographic field studies aboard research vessels tracking AUV (autonomous underwater vehicle) deployments\n- Interview marine biologists, AI ethicists, and shipboard crew about deep-sea autonomous decision-making protocols\n- Observe and document human-AI collaboration patterns between AUV operators and onboard scientific staff\n- Author qualitative research papers on the social dynamics of remote-monitored marine AI systems\n- Contribute to interdisciplinary publications across anthropology, marine biology, and AI ethics journals\n- Present research at conferences on STS (Science and Technology Studies), oceanography, and AI policy",
"word_count": 83
},
{
"bullet_count": 5,
"heading": "Required Qualifications",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Required Qualifications:",
"last_5_words": "and STS methodology"
},
"text": "- PhD or equivalent in cultural anthropology, STS, or qualitative sociology\n- 5+ years of ethnographic field experience preferably in scientific or industrial settings\n- Comfortable spending 4-6 weeks per year on research vessels in remote Pacific locations\n- Strong qualitative coding skills (NVivo, Atlas.ti)\n- Familiarity with AI ethics frameworks and STS methodology",
"word_count": 56
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "AUV"
},
{
"is_primary": true,
"skill_name": "NVivo"
},
{
"is_primary": true,
"skill_name": "Atlas.ti"
},
{
"is_primary": true,
"skill_name": "AI ethics"
},
{
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"skill_name": "STS"
}
],
"jd_role": {
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"rationale": null,
"role_aliases": [
"Ethnographer",
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],
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"slug": ""
},
"nano_parsed": {
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"about_company": null,
"certifications": [],
"company_name": "PacificAI Research Institute",
"ctc": null,
"domain": {
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],
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},
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"raw": "PhD or equivalent in cultural anthropology, STS, or qualitative sociology",
"requirement": "required"
}
],
"experience": {
"max": null,
"min": 5,
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},
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],
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"role_aliases": [
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],
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"roles_and_responsibilities": [
{
"bullet_count": 6,
"heading": "Key Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Key Responsibilities:",
"last_5_words": "oceanography, and AI policy"
},
"text": "- Conduct ethnographic field studies aboard research vessels tracking AUV (autonomous underwater vehicle) deployments\n- Interview marine biologists, AI ethicists, and shipboard crew about deep-sea autonomous decision-making protocols\n- Observe and document human-AI collaboration patterns between AUV operators and onboard scientific staff\n- Author qualitative research papers on the social dynamics of remote-monitored marine AI systems\n- Contribute to interdisciplinary publications across anthropology, marine biology, and AI ethics journals\n- Present research at conferences on STS (Science and Technology Studies), oceanography, and AI policy",
"word_count": 83
},
{
"bullet_count": 5,
"heading": "Required Qualifications",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Required Qualifications:",
"last_5_words": "and STS methodology"
},
"text": "- PhD or equivalent in cultural anthropology, STS, or qualitative sociology\n- 5+ years of ethnographic field experience preferably in scientific or industrial settings\n- Comfortable spending 4-6 weeks per year on research vessels in remote Pacific locations\n- Strong qualitative coding skills (NVivo, Atlas.ti)\n- Familiarity with AI ethics frameworks and STS methodology",
"word_count": 56
}
],
"urls": []
},
"rejected": false,
"rejection_reason": null,
"run_id": "cfa4106d-4dd9-4101-b2db-9a97bdf6a434",
"stage3_signals": {
"alias_found": false,
"alias_match_roles": [],
"kra_match_roles": [
{
"display_name": "AI Compliance Officer",
"kra_matches": [
{
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"sentence": "Familiarity with AI ethics frameworks and STS methodology",
"similarity": 0.5399
},
{
"kra_text": "Reviews AI use cases and model deployments against applicable regulations, internal ethics policies, and governance guidelines prior to production approval.",
"sentence": "Interview marine biologists, AI ethicists, and shipboard crew about deep-sea autonomous decision-making protocols",
"similarity": 0.4649
},
{
"kra_text": "Monitors deployed AI systems for compliance policy drift, regulatory changes, and emerging requirements affecting existing AI deployments.",
"sentence": "Observe and document human-AI collaboration patterns between AUV operators and onboard scientific staff",
"similarity": 0.4591
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 12,
"score": 0.488,
"slug": "ai-compliance-officer",
"total_count": null
},
{
"display_name": "AI Engineer",
"kra_matches": [
{
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"sentence": "Familiarity with AI ethics frameworks and STS methodology",
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},
{
"kra_text": "Documents AI feature capabilities, known limitations, failure modes, prompt versioning, and operational runbooks for engineering and product teams.",
"sentence": "Observe and document human-AI collaboration patterns between AUV operators and onboard scientific staff",
"similarity": 0.4314
},
{
"kra_text": "Integrates AI model API responses with application business logic, database writes, event publishing, and downstream service orchestration.",
"sentence": "Contribute to interdisciplinary publications across anthropology, marine biology, and AI ethics journals",
"similarity": 0.409
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 13,
"score": 0.4276,
"slug": "ai-engineer",
"total_count": null
},
{
"display_name": "AR/VR Engineer",
"kra_matches": [
{
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"sentence": "Observe and document human-AI collaboration patterns between AUV operators and onboard scientific staff",
"similarity": 0.4049
},
{
"kra_text": "Debugs visual artifacts, tracking jitter, controller input latency, and interaction edge cases in immersive XR application experiences.",
"sentence": "Conduct ethnographic field studies aboard research vessels tracking AUV (autonomous underwater vehicle) deployments",
"similarity": 0.338
},
{
"kra_text": "Develops room-scale locomotion systems, 6DoF interaction mechanics, and comfort-aware movement patterns for immersive VR experiences.",
"sentence": "Interview marine biologists, AI ethicists, and shipboard crew about deep-sea autonomous decision-making protocols",
"similarity": 0.3268
}
],
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},
{
"display_name": "ML Engineer",
"kra_matches": [
{
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"sentence": "Observe and document human-AI collaboration patterns between AUV operators and onboard scientific staff",
"similarity": 0.3424
},
{
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"sentence": "Familiarity with AI ethics frameworks and STS methodology",
"similarity": 0.3204
},
{
"kra_text": "Designs end-to-end ML training pipelines and model inference workflows using TensorFlow, PyTorch, or scikit-learn on cloud ML platforms.",
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}
],
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"role_id": 3,
"score": 0.3163,
"slug": "ml-engineer",
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},
{
"display_name": "ML Ops Engineer",
"kra_matches": [
{
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"sentence": "Observe and document human-AI collaboration patterns between AUV operators and onboard scientific staff",
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},
{
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"sentence": "Interview marine biologists, AI ethicists, and shipboard crew about deep-sea autonomous decision-making protocols",
"similarity": 0.3169
},
{
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"sentence": "Familiarity with AI ethics frameworks and STS methodology",
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}
],
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}
],
"skill_match_roles": []
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "A",
"chosen_role": {
"display_name": "AI Compliance Officer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 12,
"score": 0.488,
"slug": "ai-compliance-officer",
"total_count": null
},
"confidence": 0.4148,
"is_new_role": false,
"llm2_fired": false,
"llm2_reasoning": null,
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Top KRA ai-compliance-officer stands; no contradicting signal"
},
"stage5_updates": {
"centroid_n_after": 6,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": null,
"new_skills_attached": [
{
"is_primary": true,
"queue_id": 2011,
"role_display_name": "AI Compliance Officer",
"role_slug": "ai-compliance-officer",
"skill_name": "AUV",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 2012,
"role_display_name": "AI Compliance Officer",
"role_slug": "ai-compliance-officer",
"skill_name": "NVivo",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 2013,
"role_display_name": "AI Compliance Officer",
"role_slug": "ai-compliance-officer",
"skill_name": "Atlas.ti",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 2014,
"role_display_name": "AI Compliance Officer",
"role_slug": "ai-compliance-officer",
"skill_name": "AI ethics",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 2015,
"role_display_name": "AI Compliance Officer",
"role_slug": "ai-compliance-officer",
"skill_name": "STS",
"status": "pending"
}
],
"queue_entry_id": null,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": 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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