Pipeline run

b743f951-55d2-4ce7-9af6-553a560c2cd8

Pipeline LLM cost (USD)

API 1: $0.0039 API 2: $0.0000 API 3: $0.0000 Total: $0.0039

Client output enrichment

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

Nature of work · AI/ML Engineer / Data Scientist

Build and run scalable AI/ML data and feature/deployment pipelines, lead ML design reviews and production best practices, and develop real-time anomaly/threat detection and UEBA systems in Python. Also communicate technical plans across teams and help shape data-intelligence use cases.

"“Develop and maintain scalable data pipelines for various AI/ML-driven data services”"

Tech stack maturity

Mainstream Modern cache hit

The stack centers on widely adopted modern data and ML tooling like Python, Kafka, Elasticsearch, scikit-learn, TensorFlow, and PyTorch, which are current mainstream technologies rather than bleeding-edge or legacy.

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): LLM, LLMs, AI, ML, AI/ML, GenAI, Machine Learning

Evidence — skills matched in JD (20)

Python scikit-learn TensorFlow PyTorch LLM GenAI Time Series Analysis Anomaly Detection Classification Clustering Optimization AIOps Statistics Probability Machine Learning AI Model Deployment Elasticsearch Kafka SIEM SOAR

Skill cluster (8 dimension groups, role-scoped)

AI Governance and Model Security

Machine Learning

Asynchronous Messaging and Event Streaming

Kafka

Model Fine-Tuning & Adaptation

PyTorch

Model Monitoring and Drift Detection

Anomaly Detection

Performance and Cost Optimization

Clustering

Python Programming

Python

Search and Content Discovery

Elasticsearch

Cross-cutting / unaligned

scikit-learn TensorFlow LLM GenAI Time Series Analysis Classification Optimization AIOps Statistics Probability AI Model Deployment SIEM SOAR

Show KRA description ↓

• Develop and maintain scalable data pipelines for various AI/ML-driven data services, ensuring reliable data ingestion, transformation, and integration from various sources, as well as maintaining ML feature and deployment pipelines. • Ensure that data architectures and infrastructure can scale seamlessly as the data volume and complexity grow. • Oversee ML design reviews, create best practices, and develop playbooks for end-to-end ML systems in production. • Lead the development of UEBA, Anomaly detection, Threat detection etc., leveraging the available subject matter expertise and with independent research where required. • Work with a great deal of autonomy and be the technical thought leader in creating a forward-looking vision with clear direction. • Effectively communicate complex technical artifacts to both technical (engineers & scientists) and non-technical audiences. • Collaborate closely with cross-functional teams, including business stakeholders, to innovate and unlock new use cases for our customers driven by data intelligence. • Minimum of 6 years of industry experience as AI/ML Engineer or Data Scientist role, with hands-on development experience. • Hands-on expertise in Time Series Analysis, behavior analytics, and real-time analysis. • Demonstrated experience in AI projects, including familiarity with AI and machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch, LLMs, GenAI). • Proficiency in Python programming. • Skills in anomaly detection, classification, clustering, optimization, and AI/AIOps and Knowledge in statistics, probability, and other mathematical concepts underlying them. • Knowledge in AI model deployment and integration. • Strong problem-solving capabilities, with the ability to adapt to a dynamic, fast-paced environment. • Excellent communication and teamwork abilities. • Advanced experience with technologies including Elasticsearch, Kafka, SIEM, SOAR, real-time data aggregation, and enrichment. • Good understanding of enterprise cybersecurity landscape and security related data. • Experience in design and technical leadership.

Signals

Skill data-engineer

0.20

Alias ml-engineer

0.48

KRA ai-compliance-officer

0.44

Post-classification

Centroidupdated · n=11

Alias collision log—

New-role queue—

New skills captured13

New KRA captured—

Captured for admin review

LLM primary ↔ AI Engineer pending

GenAI primary ↔ AI Engineer pending

Time Series Analysis primary ↔ AI Engineer pending

Classification primary ↔ AI Engineer pending

Optimization primary ↔ AI Engineer pending

AIOps primary ↔ AI Engineer pending

Statistics primary ↔ AI Engineer pending

Probability primary ↔ AI Engineer pending

Machine Learning primary ↔ AI Engineer pending

AI Model Deployment primary ↔ AI Engineer pending

Elasticsearch primary ↔ AI Engineer pending

SIEM primary ↔ AI Engineer pending

SOAR primary ↔ AI Engineer pending

Status: extract_from_jd_done Created: 2026-05-19T00:51:30.954692Z Updated: 2026-05-19T00:51:32.059484Z

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

Principal AI/ML Engineer

Job description
Position: Principal AI/ML Engineer
Exp: 6+ years
Base Location: Hyderabad, Telangana
Notice Period: Immediate to 30 Days


The Principal AI/ML Engineer will be responsible for architecting and building data and ML pipelines across Cybersecurity and IT compliance segment. The ideal candidate is expected to work hands-on and possess deep subject matter expertise in AI/ML infrastructure and platforms. This role is responsible for end-to-end AI/ML operations.


Job Requirements:


• Minimum of 6 years of industry experience as AI/ML Engineer or Data Scientist role, with hands-on development experience.
• Hands-on expertise in Time Series Analysis, behavior analytics, and real-time analysis.
• Demonstrated experience in AI projects, including familiarity with AI and machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch, LLMs, GenAI).
• Proficiency in Python programming.
• Skills in anomaly detection, classification, clustering, optimization, and AI/AIOps and Knowledge in statistics, probability, and other mathematical concepts underlying them.
• Knowledge in AI model deployment and integration.
• Strong problem-solving capabilities, with the ability to adapt to a dynamic, fast-paced environment.
• Excellent communication and teamwork abilities


Job Responsibilities:


• Develop and maintain scalable data pipelines for various AI/ML-driven data services, ensuring reliable data ingestion, transformation, and integration from various sources, as well as maintaining ML feature and deployment pipelines.
• Ensure that data architectures and infrastructure can scale seamlessly as the data volume and complexity grow.
• Oversee ML design reviews, create best practices, and develop playbooks for end-to-end ML systems in production.
• Lead the development of UEBA, Anomaly detection, Threat detection etc., leveraging the available subject matter expertise and with independent research where required.
• Work with a great deal of autonomy and be the technical thought leader in creating a forward-looking vision with clear direction.
• Effectively communicate complex technical artifacts to both technical (engineers & scientists) and non-technical audiences.
• Collaborate closely with cross-functional teams, including business stakeholders, to innovate and unlock new use cases for our customers driven by data intelligence.


Preferred Technical and Professional Expertise:


• Advanced experience with technologies including Elasticsearch, Kafka, SIEM, SOAR, real-time data aggregation, and enrichment.
• Good understanding of enterprise cybersecurity landscape and security related data.
• Experience in design and technical leadership.

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)

scikit-learn Primary No API 2 row (run stopped after API 1 or history missing)

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

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

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

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

Time Series Analysis Primary No API 2 row (run stopped after API 1 or history missing)

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

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

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

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

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

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

Probability 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)

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

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

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

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

SOAR 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

RolePrincipal AI/ML Engineer

Experience6+ years

DomainCybersecurity

Location Hyderabad, India

JD type pass

Show raw JSON

{
  "JD_type": "pass",
  "about_company": null,
  "certifications": [],
  "company_name": null,
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [
        "IT Security",
        "Information Security"
      ],
      "domain": "Cybersecurity"
    },
    "secondary": null
  },
  "education": [],
  "experience": {
    "max": null,
    "min": 6,
    "raw": "6+ years"
  },
  "job_locations": [
    {
      "aliases": [
        "Hyderabad, TG"
      ],
      "city": "Hyderabad",
      "country": "India",
      "state": "Telangana",
      "work_mode": null
    }
  ],
  "role": "Principal AI/ML Engineer",
  "role_archetype": "Data",
  "roles_and_responsibilities": [
    {
      "bullet_count": 7,
      "heading": "Job Responsibilities",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Develop and maintain scalable",
        "last_5_words": "driven by data intelligence."
      },
      "text": "\u2022 Develop and maintain scalable data pipelines for various AI/ML-driven data services, ensuring reliable data ingestion, transformation, and integration from various sources, as well as maintaining ML feature and deployment pipelines.\n\u2022 Ensure that data architectures and infrastructure can scale seamlessly as the data volume and complexity grow.\n\u2022 Oversee ML design reviews, create best practices, and develop playbooks for end-to-end ML systems in production.\n\u2022 Lead the development of UEBA, Anomaly detection, Threat detection etc., leveraging the available subject matter expertise and with independent research where required.\n\u2022 Work with a great deal of autonomy and be the technical thought leader in creating a forward-looking vision with clear direction.\n\u2022 Effectively communicate complex technical artifacts to both technical (engineers \u0026 scientists) and non-technical audiences.\n\u2022 Collaborate closely with cross-functional teams, including business stakeholders, to innovate and unlock new use cases for our customers driven by data intelligence.",
      "word_count": 164
    },
    {
      "bullet_count": 8,
      "heading": "Job Requirements",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Minimum of 6 years",
        "last_5_words": "communication and teamwork abilities."
      },
      "text": "\u2022 Minimum of 6 years of industry experience as AI/ML Engineer or Data Scientist role, with hands-on development experience.\n\u2022 Hands-on expertise in Time Series Analysis, behavior analytics, and real-time analysis.\n\u2022 Demonstrated experience in AI projects, including familiarity with AI and machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch, LLMs, GenAI).\n\u2022 Proficiency in Python programming.\n\u2022 Skills in anomaly detection, classification, clustering, optimization, and AI/AIOps and Knowledge in statistics, probability, and other mathematical concepts underlying them.\n\u2022 Knowledge in AI model deployment and integration.\n\u2022 Strong problem-solving capabilities, with the ability to adapt to a dynamic, fast-paced environment.\n\u2022 Excellent communication and teamwork abilities.",
      "word_count": 139
    },
    {
      "bullet_count": 3,
      "heading": "Preferred Technical and Professional Expertise",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Advanced experience with technologies",
        "last_5_words": "design and technical leadership."
      },
      "text": "\u2022 Advanced experience with technologies including Elasticsearch, Kafka, SIEM, SOAR, real-time data aggregation, and enrichment.\n\u2022 Good understanding of enterprise cybersecurity landscape and security related data.\n\u2022 Experience in design and technical leadership.",
      "word_count": 45
    }
  ],
  "urls": []
}

API 1 — extract-from-jd click to toggle

{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Python"
    },
    {
      "is_primary": true,
      "skill_name": "scikit-learn"
    },
    {
      "is_primary": true,
      "skill_name": "TensorFlow"
    },
    {
      "is_primary": true,
      "skill_name": "PyTorch"
    },
    {
      "is_primary": true,
      "skill_name": "LLM"
    },
    {
      "is_primary": true,
      "skill_name": "GenAI"
    },
    {
      "is_primary": true,
      "skill_name": "Time Series Analysis"
    },
    {
      "is_primary": true,
      "skill_name": "Anomaly Detection"
    },
    {
      "is_primary": true,
      "skill_name": "Classification"
    },
    {
      "is_primary": true,
      "skill_name": "Clustering"
    },
    {
      "is_primary": true,
      "skill_name": "Optimization"
    },
    {
      "is_primary": true,
      "skill_name": "AIOps"
    },
    {
      "is_primary": true,
      "skill_name": "Statistics"
    },
    {
      "is_primary": true,
      "skill_name": "Probability"
    },
    {
      "is_primary": true,
      "skill_name": "Machine Learning"
    },
    {
      "is_primary": true,
      "skill_name": "AI Model Deployment"
    },
    {
      "is_primary": true,
      "skill_name": "Elasticsearch"
    },
    {
      "is_primary": true,
      "skill_name": "Kafka"
    },
    {
      "is_primary": true,
      "skill_name": "SIEM"
    },
    {
      "is_primary": true,
      "skill_name": "SOAR"
    }
  ],
  "jd_role": {
    "display_name": "Principal AI/ML Engineer",
    "rationale": null,
    "role_archetype": "Data",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": null,
    "certifications": [],
    "company_name": null,
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [
          "IT Security",
          "Information Security"
        ],
        "domain": "Cybersecurity"
      },
      "secondary": null
    },
    "education": [],
    "experience": {
      "max": null,
      "min": 6,
      "raw": "6+ years"
    },
    "job_locations": [
      {
        "aliases": [
          "Hyderabad, TG"
        ],
        "city": "Hyderabad",
        "country": "India",
        "state": "Telangana",
        "work_mode": null
      }
    ],
    "role": "Principal AI/ML Engineer",
    "role_archetype": "Data",
    "roles_and_responsibilities": [
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        "heading": "Job Responsibilities",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Develop and maintain scalable",
          "last_5_words": "driven by data intelligence."
        },
        "text": "\u2022 Develop and maintain scalable data pipelines for various AI/ML-driven data services, ensuring reliable data ingestion, transformation, and integration from various sources, as well as maintaining ML feature and deployment pipelines.\n\u2022 Ensure that data architectures and infrastructure can scale seamlessly as the data volume and complexity grow.\n\u2022 Oversee ML design reviews, create best practices, and develop playbooks for end-to-end ML systems in production.\n\u2022 Lead the development of UEBA, Anomaly detection, Threat detection etc., leveraging the available subject matter expertise and with independent research where required.\n\u2022 Work with a great deal of autonomy and be the technical thought leader in creating a forward-looking vision with clear direction.\n\u2022 Effectively communicate complex technical artifacts to both technical (engineers \u0026 scientists) and non-technical audiences.\n\u2022 Collaborate closely with cross-functional teams, including business stakeholders, to innovate and unlock new use cases for our customers driven by data intelligence.",
        "word_count": 164
      },
      {
        "bullet_count": 8,
        "heading": "Job Requirements",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Minimum of 6 years",
          "last_5_words": "communication and teamwork abilities."
        },
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        "word_count": 139
      },
      {
        "bullet_count": 3,
        "heading": "Preferred Technical and Professional Expertise",
        "heading_was_present": true,
        "source_marker": {
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          "last_5_words": "design and technical leadership."
        },
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        "word_count": 45
      }
    ],
    "urls": []
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "b743f951-55d2-4ce7-9af6-553a560c2cd8",
  "stage3_signals": {
    "alias_match_roles": [
      {
        "display_name": "ML Engineer",
        "matched_count": null,
        "role_id": 3,
        "score": 0.48,
        "slug": "ml-engineer",
        "total_count": null
      },
      {
        "display_name": "AI Engineer",
        "matched_count": null,
        "role_id": 13,
        "score": 0.48,
        "slug": "ai-engineer",
        "total_count": null
      },
      {
        "display_name": "AR/VR Engineer",
        "matched_count": null,
        "role_id": 8,
        "score": 0.3704,
        "slug": "ar-vr-engineer",
        "total_count": null
      },
      {
        "display_name": "Frontend Engineer",
        "matched_count": null,
        "role_id": 7,
        "score": 0.3214,
        "slug": "frontend-engineer",
        "total_count": null
      },
      {
        "display_name": "Ios engineer",
        "matched_count": null,
        "role_id": 6,
        "score": 0.3143,
        "slug": "ios-engineer",
        "total_count": null
      }
    ],
    "kra_match_roles": [
      {
        "display_name": "AI Compliance Officer",
        "matched_count": null,
        "role_id": 12,
        "score": 0.4369,
        "slug": "ai-compliance-officer",
        "total_count": null
      },
      {
        "display_name": "AI Engineer",
        "matched_count": null,
        "role_id": 13,
        "score": 0.4106,
        "slug": "ai-engineer",
        "total_count": null
      },
      {
        "display_name": "Android Engineer",
        "matched_count": null,
        "role_id": 4,
        "score": 0.4105,
        "slug": "android-engineer",
        "total_count": null
      },
      {
        "display_name": "ML Engineer",
        "matched_count": null,
        "role_id": 3,
        "score": 0.4025,
        "slug": "ml-engineer",
        "total_count": null
      },
      {
        "display_name": "Cybersecurity Engineer",
        "matched_count": null,
        "role_id": 5,
        "score": 0.3796,
        "slug": "cybersecurity-engineer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Data Engineer",
        "matched_count": 4,
        "role_id": 2,
        "score": 0.2,
        "slug": "data-engineer",
        "total_count": 20
      },
      {
        "display_name": "ML Engineer",
        "matched_count": 4,
        "role_id": 3,
        "score": 0.2,
        "slug": "ml-engineer",
        "total_count": 20
      },
      {
        "display_name": "Backend Engineer",
        "matched_count": 2,
        "role_id": 1,
        "score": 0.1,
        "slug": "backend-engineer",
        "total_count": 20
      },
      {
        "display_name": "Cybersecurity Engineer",
        "matched_count": 1,
        "role_id": 5,
        "score": 0.05,
        "slug": "cybersecurity-engineer",
        "total_count": 20
      },
      {
        "display_name": "AR/VR Engineer",
        "matched_count": 1,
        "role_id": 8,
        "score": 0.05,
        "slug": "ar-vr-engineer",
        "total_count": 20
      }
    ],
    "stage35_ran": false
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "A",
    "chosen_role": {
      "display_name": "AI Engineer",
      "matched_count": null,
      "role_id": 13,
      "score": 1.0,
      "slug": "ai-engineer",
      "total_count": null
    },
    "confidence": 0.4106,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "queued": false,
    "reasoning": "Stage 1 title \u0027AI Engineer\u0027 (embedding match, sim 0.86); KRA agrees (0.41)"
  },
  "stage5_updates": {
    "centroid_n_after": 11,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 792,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "LLM",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 793,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "GenAI",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 794,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Time Series Analysis",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 795,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Classification",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 796,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Optimization",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 797,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "AIOps",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 798,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Statistics",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 799,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Probability",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 800,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Machine Learning",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 801,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "AI Model Deployment",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 802,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Elasticsearch",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 803,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "SIEM",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 804,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "SOAR",
        "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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