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Pipeline run

af5a6b8d-8c9d-4c64-ac9e-11ec0acf4789

Pipeline LLM cost (USD)

API 1: $0.0037 API 2: $0.0000 API 3: $0.0000 Total: $0.0037

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)

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): LangChain, LlamaIndex, Hugging Face, Azure OpenAI, CrewAI, Pinecone

Models / concepts (×3): Anthropic, OpenAI, RAG, LLMs, MLOps, AI

Evidence — skills matched in JD (24)

Python SQL Snowflake Pinecone FAISS ChromaDB LangChain LlamaIndex OpenAI Azure OpenAI Anthropic Hugging Face PostgreSQL MySQL Git CI/CD Docker MLflow AWS Azure GCP CrewAI Power BI Tableau

Skill cluster (0 dimension groups, role-scoped)

No dimension groups computed for this JD.

Show KRA description ↓

- Design and build AI-powered applications and conversational agents using LLMs to interact with structured data sources (SQL databases, Snowflake) - Develop RAG pipelines using vector stores (Pinecone, FAISS, ChromaDB) - Integrate frameworks like LangChain, LlamaIndex, CrewAI - Work with OpenAI, Azure OpenAI, Anthropic, Hugging Face APIs - Set up MLOps practices (model versioning, MLflow) Python, SQL, Snowflake, Pinecone, FAISS, ChromaDB, LangChain, LlamaIndex, OpenAI, Azure OpenAI, Anthropic, Hugging Face, PostgreSQL, MySQL, Git, CI/CD, Docker, MLflow, AWS, Azure, GCP, Power BI, Tableau, CrewAI

Signals

Skill ml-engineer

0.50

Alias ar-vr-engineer

0.71

KRA ai-compliance-officer

0.47

Post-classification

Centroid—

Alias collision log—

New-role queue#28

New skills captured0

New KRA captured—

Status: extract_from_jd_done Created: 2026-05-18T22:48:43.808374Z Updated: 2026-05-18T22:48:44.339004Z

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 Engineer

Join us in building intelligent, AI-driven applications that transform how users interact with data. We are looking for a hands-on AI Engineer with 2-3 years of experience who is excited about working with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and conversational AI systems.

Responsibilities
- Design and build AI-powered applications and conversational agents using LLMs to interact with structured data sources (SQL databases, Snowflake)
- Develop RAG pipelines using vector stores (Pinecone, FAISS, ChromaDB)
- Integrate frameworks like LangChain, LlamaIndex, CrewAI
- Work with OpenAI, Azure OpenAI, Anthropic, Hugging Face APIs
- Set up MLOps practices (model versioning, MLflow)

Required skills: Python, SQL, Snowflake, Pinecone, FAISS, ChromaDB, LangChain, LlamaIndex, OpenAI, Azure OpenAI, Anthropic, Hugging Face, PostgreSQL, MySQL, Git, CI/CD, Docker, MLflow, AWS, Azure, GCP, Power BI, Tableau, CrewAI

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)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

CI/CD Primary No API 2 row (run stopped after API 1 or history missing)

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

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

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

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

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

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

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

CrewAI 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 Engineer

Experience2-3 years of experience

DomainSoftware & SaaS Products

JD type pass

Show raw JSON

{
  "JD_type": "pass",
  "about_company": null,
  "certifications": [],
  "company_name": null,
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [
        "SaaS",
        "Product Companies"
      ],
      "domain": "Software \u0026 SaaS Products"
    },
    "secondary": null
  },
  "education": [],
  "experience": {
    "max": 3,
    "min": 2,
    "raw": "2-3 years of experience"
  },
  "job_locations": [],
  "role": "AI Engineer",
  "role_archetype": "Engineering",
  "roles_and_responsibilities": [
    {
      "bullet_count": 5,
      "heading": "Responsibilities",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Responsibilities\n- Design and build",
        "last_5_words": "versioning, MLflow)"
      },
      "text": "- Design and build AI-powered applications and conversational agents using LLMs to interact with structured data sources (SQL databases, Snowflake)\n- Develop RAG pipelines using vector stores (Pinecone, FAISS, ChromaDB)\n- Integrate frameworks like LangChain, LlamaIndex, CrewAI\n- Work with OpenAI, Azure OpenAI, Anthropic, Hugging Face APIs\n- Set up MLOps practices (model versioning, MLflow)",
      "word_count": 54
    },
    {
      "bullet_count": 0,
      "heading": "Required skills",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Required skills: Python, SQL,",
        "last_5_words": "Power BI, Tableau, CrewAI"
      },
      "text": "Python, SQL, Snowflake, Pinecone, FAISS, ChromaDB, LangChain, LlamaIndex, OpenAI, Azure OpenAI, Anthropic, Hugging Face, PostgreSQL, MySQL, Git, CI/CD, Docker, MLflow, AWS, Azure, GCP, Power BI, Tableau, CrewAI",
      "word_count": 36
    }
  ],
  "urls": []
}

API 1 — extract-from-jd click to toggle

{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Python"
    },
    {
      "is_primary": true,
      "skill_name": "SQL"
    },
    {
      "is_primary": true,
      "skill_name": "Snowflake"
    },
    {
      "is_primary": true,
      "skill_name": "Pinecone"
    },
    {
      "is_primary": true,
      "skill_name": "FAISS"
    },
    {
      "is_primary": true,
      "skill_name": "ChromaDB"
    },
    {
      "is_primary": true,
      "skill_name": "LangChain"
    },
    {
      "is_primary": true,
      "skill_name": "LlamaIndex"
    },
    {
      "is_primary": true,
      "skill_name": "OpenAI"
    },
    {
      "is_primary": true,
      "skill_name": "Azure OpenAI"
    },
    {
      "is_primary": true,
      "skill_name": "Anthropic"
    },
    {
      "is_primary": true,
      "skill_name": "Hugging Face"
    },
    {
      "is_primary": true,
      "skill_name": "PostgreSQL"
    },
    {
      "is_primary": true,
      "skill_name": "MySQL"
    },
    {
      "is_primary": true,
      "skill_name": "Git"
    },
    {
      "is_primary": true,
      "skill_name": "CI/CD"
    },
    {
      "is_primary": true,
      "skill_name": "Docker"
    },
    {
      "is_primary": true,
      "skill_name": "MLflow"
    },
    {
      "is_primary": true,
      "skill_name": "AWS"
    },
    {
      "is_primary": true,
      "skill_name": "Azure"
    },
    {
      "is_primary": true,
      "skill_name": "GCP"
    },
    {
      "is_primary": false,
      "skill_name": "Power BI"
    },
    {
      "is_primary": false,
      "skill_name": "Tableau"
    },
    {
      "is_primary": true,
      "skill_name": "CrewAI"
    }
  ],
  "jd_role": {
    "display_name": "AI Engineer",
    "rationale": null,
    "role_archetype": "Engineering",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": null,
    "certifications": [],
    "company_name": null,
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [
          "SaaS",
          "Product Companies"
        ],
        "domain": "Software \u0026 SaaS Products"
      },
      "secondary": null
    },
    "education": [],
    "experience": {
      "max": 3,
      "min": 2,
      "raw": "2-3 years of experience"
    },
    "job_locations": [],
    "role": "AI Engineer",
    "role_archetype": "Engineering",
    "roles_and_responsibilities": [
      {
        "bullet_count": 5,
        "heading": "Responsibilities",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "Responsibilities\n- Design and build",
          "last_5_words": "versioning, MLflow)"
        },
        "text": "- Design and build AI-powered applications and conversational agents using LLMs to interact with structured data sources (SQL databases, Snowflake)\n- Develop RAG pipelines using vector stores (Pinecone, FAISS, ChromaDB)\n- Integrate frameworks like LangChain, LlamaIndex, CrewAI\n- Work with OpenAI, Azure OpenAI, Anthropic, Hugging Face APIs\n- Set up MLOps practices (model versioning, MLflow)",
        "word_count": 54
      },
      {
        "bullet_count": 0,
        "heading": "Required skills",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "Required skills: Python, SQL,",
          "last_5_words": "Power BI, Tableau, CrewAI"
        },
        "text": "Python, SQL, Snowflake, Pinecone, FAISS, ChromaDB, LangChain, LlamaIndex, OpenAI, Azure OpenAI, Anthropic, Hugging Face, PostgreSQL, MySQL, Git, CI/CD, Docker, MLflow, AWS, Azure, GCP, Power BI, Tableau, CrewAI",
        "word_count": 36
      }
    ],
    "urls": []
  },
  "run_id": "af5a6b8d-8c9d-4c64-ac9e-11ec0acf4789",
  "stage3_signals": {
    "alias_match_roles": [
      {
        "display_name": "AR/VR Engineer",
        "matched_count": null,
        "role_id": 8,
        "score": 0.7143,
        "slug": "ar-vr-engineer",
        "total_count": null
      },
      {
        "display_name": "Frontend Engineer",
        "matched_count": null,
        "role_id": 7,
        "score": 0.6,
        "slug": "frontend-engineer",
        "total_count": null
      },
      {
        "display_name": "ML Engineer",
        "matched_count": null,
        "role_id": 3,
        "score": 0.6,
        "slug": "ml-engineer",
        "total_count": null
      },
      {
        "display_name": "Ios engineer",
        "matched_count": null,
        "role_id": 6,
        "score": 0.5625,
        "slug": "ios-engineer",
        "total_count": null
      },
      {
        "display_name": "Data Engineer",
        "matched_count": null,
        "role_id": 2,
        "score": 0.5294,
        "slug": "data-engineer",
        "total_count": null
      }
    ],
    "kra_match_roles": [
      {
        "display_name": "AI Compliance Officer",
        "matched_count": null,
        "role_id": 12,
        "score": 0.4677,
        "slug": "ai-compliance-officer",
        "total_count": null
      },
      {
        "display_name": "Backend Engineer",
        "matched_count": null,
        "role_id": 1,
        "score": 0.4451,
        "slug": "backend-engineer",
        "total_count": null
      },
      {
        "display_name": "ML Engineer",
        "matched_count": null,
        "role_id": 3,
        "score": 0.4337,
        "slug": "ml-engineer",
        "total_count": null
      },
      {
        "display_name": "AR/VR Engineer",
        "matched_count": null,
        "role_id": 8,
        "score": 0.4154,
        "slug": "ar-vr-engineer",
        "total_count": null
      },
      {
        "display_name": "Android Engineer",
        "matched_count": null,
        "role_id": 4,
        "score": 0.4143,
        "slug": "android-engineer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "ML Engineer",
        "matched_count": 12,
        "role_id": 3,
        "score": 0.5,
        "slug": "ml-engineer",
        "total_count": 24
      },
      {
        "display_name": "Data Engineer",
        "matched_count": 9,
        "role_id": 2,
        "score": 0.375,
        "slug": "data-engineer",
        "total_count": 24
      },
      {
        "display_name": "Backend Engineer",
        "matched_count": 8,
        "role_id": 1,
        "score": 0.3333,
        "slug": "backend-engineer",
        "total_count": 24
      },
      {
        "display_name": "DevOps Engineer",
        "matched_count": 6,
        "role_id": 10,
        "score": 0.25,
        "slug": "devops-engineer",
        "total_count": 24
      },
      {
        "display_name": "Cybersecurity Engineer",
        "matched_count": 5,
        "role_id": 5,
        "score": 0.2083,
        "slug": "cybersecurity-engineer",
        "total_count": 24
      }
    ],
    "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": "small_margin: KRA margin 0.02 \u003c 0.05"
  },
  "stage5_updates": {
    "centroid_n_after": null,
    "centroid_updated": false,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [],
    "queue_entry_id": 28,
    "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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