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Pipeline run

2400f0da-09fb-41de-8cb4-db4b34d11eaa

Pipeline LLM cost (USD)

API 1: $0.0026 API 2: $0.0000 API 3: $0.0000 Total: $0.0026

Client output enrichment

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

SPARSE JD

Nature of work

—

no_db_connection

Tech stack maturity

Mainstream Modern

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

0.00 / 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): —

Evidence — skills matched in JD (6)

Python AlphaFold Rosetta Biopython SBOL CRISPR

Skill cluster (0 dimension groups, role-scoped)

No dimension groups computed for this JD.

Show KRA description ↓

We seek a Synthetic Biology Computational Scientist to design DNA constructs, optimize protein folding via AlphaFold, and develop in-silico models of metabolic pathways. Python, AlphaFold, Rosetta, BioPython, SBOL, gene circuit simulation, CRISPR design

Signals

Skill backend-engineer

0.17

Alias —

—

KRA ml-engineer

0.36

Post-classification

Centroid—

Alias collision log—

New-role queue#29

New skills captured0

New KRA captured—

Status: extract_from_jd_done Created: 2026-05-18T22:56:55.432712Z Updated: 2026-05-18T22:56:56.919472Z

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

Synthetic Biology Computational Scientist

We seek a Synthetic Biology Computational Scientist to design DNA constructs, optimize protein folding via AlphaFold, and develop in-silico models of metabolic pathways.

Required: Python, AlphaFold, Rosetta, BioPython, SBOL, gene circuit simulation, CRISPR design

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

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

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

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

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

CRISPR 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

RoleSynthetic Biology Computational Scientist

DomainOther

JD type pass

Show raw JSON

{
  "JD_type": "pass",
  "about_company": null,
  "certifications": [],
  "company_name": null,
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [],
      "domain": "Other"
    },
    "secondary": null
  },
  "education": [],
  "experience": {
    "max": null,
    "min": null,
    "raw": null
  },
  "job_locations": [],
  "role": "Synthetic Biology Computational Scientist",
  "role_archetype": "Other",
  "roles_and_responsibilities": [
    {
      "bullet_count": 0,
      "heading": "Role Overview",
      "heading_was_present": false,
      "source_marker": {
        "first_5_words": "We seek a Synthetic Biology",
        "last_5_words": "models of metabolic pathways."
      },
      "text": "We seek a Synthetic Biology Computational Scientist to design DNA constructs, optimize protein folding via AlphaFold, and develop in-silico models of metabolic pathways.",
      "word_count": 25
    },
    {
      "bullet_count": 0,
      "heading": "Required",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Python, AlphaFold, Rosetta, BioPython,",
        "last_5_words": "circuit simulation, CRISPR design"
      },
      "text": "Python, AlphaFold, Rosetta, BioPython, SBOL, gene circuit simulation, CRISPR design",
      "word_count": 13
    }
  ],
  "urls": []
}

API 1 — extract-from-jd click to toggle

{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Python"
    },
    {
      "is_primary": true,
      "skill_name": "AlphaFold"
    },
    {
      "is_primary": true,
      "skill_name": "Rosetta"
    },
    {
      "is_primary": true,
      "skill_name": "Biopython"
    },
    {
      "is_primary": true,
      "skill_name": "SBOL"
    },
    {
      "is_primary": true,
      "skill_name": "CRISPR"
    }
  ],
  "jd_role": {
    "display_name": "Synthetic Biology Computational Scientist",
    "rationale": null,
    "role_archetype": "Other",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": null,
    "certifications": [],
    "company_name": null,
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [],
        "domain": "Other"
      },
      "secondary": null
    },
    "education": [],
    "experience": {
      "max": null,
      "min": null,
      "raw": null
    },
    "job_locations": [],
    "role": "Synthetic Biology Computational Scientist",
    "role_archetype": "Other",
    "roles_and_responsibilities": [
      {
        "bullet_count": 0,
        "heading": "Role Overview",
        "heading_was_present": false,
        "source_marker": {
          "first_5_words": "We seek a Synthetic Biology",
          "last_5_words": "models of metabolic pathways."
        },
        "text": "We seek a Synthetic Biology Computational Scientist to design DNA constructs, optimize protein folding via AlphaFold, and develop in-silico models of metabolic pathways.",
        "word_count": 25
      },
      {
        "bullet_count": 0,
        "heading": "Required",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "Python, AlphaFold, Rosetta, BioPython,",
          "last_5_words": "circuit simulation, CRISPR design"
        },
        "text": "Python, AlphaFold, Rosetta, BioPython, SBOL, gene circuit simulation, CRISPR design",
        "word_count": 13
      }
    ],
    "urls": []
  },
  "run_id": "2400f0da-09fb-41de-8cb4-db4b34d11eaa",
  "stage3_signals": {
    "alias_match_roles": [],
    "kra_match_roles": [
      {
        "display_name": "ML Engineer",
        "matched_count": null,
        "role_id": 3,
        "score": 0.3617,
        "slug": "ml-engineer",
        "total_count": null
      },
      {
        "display_name": "Data Engineer",
        "matched_count": null,
        "role_id": 2,
        "score": 0.3167,
        "slug": "data-engineer",
        "total_count": null
      },
      {
        "display_name": "AI Compliance Officer",
        "matched_count": null,
        "role_id": 12,
        "score": 0.2795,
        "slug": "ai-compliance-officer",
        "total_count": null
      },
      {
        "display_name": "DevOps Engineer",
        "matched_count": null,
        "role_id": 10,
        "score": 0.2702,
        "slug": "devops-engineer",
        "total_count": null
      },
      {
        "display_name": "Android Engineer",
        "matched_count": null,
        "role_id": 4,
        "score": 0.2345,
        "slug": "android-engineer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Backend Engineer",
        "matched_count": 1,
        "role_id": 1,
        "score": 0.1667,
        "slug": "backend-engineer",
        "total_count": 6
      },
      {
        "display_name": "Data Engineer",
        "matched_count": 1,
        "role_id": 2,
        "score": 0.1667,
        "slug": "data-engineer",
        "total_count": 6
      },
      {
        "display_name": "ML Engineer",
        "matched_count": 1,
        "role_id": 3,
        "score": 0.1667,
        "slug": "ml-engineer",
        "total_count": 6
      },
      {
        "display_name": "Cybersecurity Engineer",
        "matched_count": 1,
        "role_id": 5,
        "score": 0.1667,
        "slug": "cybersecurity-engineer",
        "total_count": 6
      },
      {
        "display_name": "AR/VR Engineer",
        "matched_count": 1,
        "role_id": 8,
        "score": 0.1667,
        "slug": "ar-vr-engineer",
        "total_count": 6
      }
    ],
    "stage35_ran": false
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "E",
    "chosen_role": null,
    "confidence": 0.0,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "queued": true,
    "reasoning": "low_kra: top KRA 0.36 \u003c 0.4"
  },
  "stage5_updates": {
    "centroid_n_after": null,
    "centroid_updated": false,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [],
    "queue_entry_id": 29,
    "v3_pipeline_triggered": true,
    "v3_role_slug": "synthetic-biology-computational-scientist",
    "v3_run_id": "8c2f76e2-4a67-4a4f-8772-b472e2b80e7c"
  }
}

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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