Pipeline run

32ec9037-374c-4fcc-8b5f-e78ae4327242

Pipeline LLM cost (USD)

API 1: $0.0043 API 2: $0.0000 API 3: $0.0000 Total: $0.0043

Client output enrichment

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

Nature of work · AI/ML Engineering

Build and run scalable Python ML/data pipelines, lead production ML design and deployment, and develop real-time anomaly/UEBA/threat detection systems using Kafka, Elasticsearch, SIEM/SOAR, and time-series analytics.

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

Tech stack maturity

Modern Cloud Native

The skill set centers on contemporary AI/ML engineering with Python, PyTorch, TensorFlow, Kafka, and Elasticsearch, which aligns most strongly with modern cloud-native data and machine learning stacks.

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

Evidence — skills matched in JD (28)

Python scikit-learn TensorFlow PyTorch Elasticsearch Kafka SIEM SOAR Time Series Analysis Anomaly Detection Classification Clustering Optimization Machine Learning AI AIOps Data Pipelines Feature Pipelines Deployment Pipelines Real-time Analysis Real-time Data Aggregation Data Integration Data Ingestion Data Transformation Statistics +3

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 SIEM SOAR Time Series Analysis Classification Optimization AI AIOps Data Pipelines Feature Pipelines Deployment Pipelines Real-time Analysis Real-time Data Aggregation Data Integration Data Ingestion Data Transformation Statistics Probability LLMs GenAI

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 ml-engineer

0.18

Alias ml-engineer

0.48

KRA ai-compliance-officer

0.44

Post-classification

Centroidupdated · n=15

Alias collision log—

New-role queue—

New skills captured18

New KRA captured—

Captured for admin review

Elasticsearch primary ↔ AI Engineer pending

SIEM primary ↔ AI Engineer pending

SOAR 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

GenAI ↔ AI Engineer pending

Data Pipelines primary ↔ AI Engineer pending

Feature Pipelines primary ↔ AI Engineer pending

Deployment Pipelines primary ↔ AI Engineer pending

Real-time Analysis primary ↔ AI Engineer pending

Real-time Data Aggregation primary ↔ AI Engineer pending

Data Integration primary ↔ AI Engineer pending

Data Ingestion primary ↔ AI Engineer pending

Data Transformation primary ↔ AI Engineer pending

Statistics primary ↔ AI Engineer pending

Probability primary ↔ AI Engineer pending

Status: extract_from_jd_done Created: 2026-05-19T11:31:24.439896Z Updated: 2026-05-19T11:31:25.637764Z

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)

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)

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)

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

AI 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)

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

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

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

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

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

Real-time Analysis Primary No API 2 row (run stopped after API 1 or history missing)

Real-time Data Aggregation Primary No API 2 row (run stopped after API 1 or history missing)

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

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

Data Transformation 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)

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

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API 1 — extract-from-jd click to toggle

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      {
        "is_primary": true,
        "queue_id": 1187,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Deployment Pipelines",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1188,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Real-time Analysis",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1189,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Real-time Data Aggregation",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1190,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Data Integration",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1191,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Data Ingestion",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1192,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Data Transformation",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1193,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Statistics",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1194,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "Probability",
        "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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