Pipeline run

92991528-b2dc-4829-a951-43016b773555

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 maintain AI/LLM backend pipelines in Python or .NET, prepping and augmenting data, working with embeddings/chunking on custom datasets, and deploying scalable models with Azure/cloud services.

"Design and develop backend services using Python or .NET to support OpenAI-powered solutions"

Tech stack maturity

Modern Cloud Native

The skill set centers on Azure, OpenAI, embeddings, and modern ML frameworks like Python, PyTorch, and TensorFlow, indicating a cloud-first, contemporary AI engineering stack.

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): OpenAI, Transformers, embeddings, LLM, NLP, computer vision, multimodal, AI, GenAI, Generative AI, Machine Learning, Deep Learning

Evidence — skills matched in JD (28)

Python .NET OpenAI Azure TensorFlow PyTorch Keras Machine Learning Deep Learning Generative AI GANs VAEs Transformers Natural Language Processing Embeddings Data Preprocessing Data Augmentation Synthetic Data AI Pipelines AWS GCP Docker Kubernetes Computer Vision Chunking +3

Skill cluster (8 dimension groups, role-scoped)

Cloud Platforms for AI Deployment

Azure AWS GCP

AI Governance and Model Security

Machine Learning

Containerization and Image Builds

Docker

Kubernetes for ML Workloads

Kubernetes

ML Frameworks and Libraries

Embeddings

Model Fine-Tuning & Adaptation

PyTorch

Python Programming

Python

Cross-cutting / unaligned

.NET OpenAI TensorFlow Keras Deep Learning Generative AI GANs VAEs Transformers Natural Language Processing Data Preprocessing Data Augmentation Synthetic Data AI Pipelines Computer Vision Chunking Text Parsing Sentiment Analysis GPT

Show KRA description ↓

• Handle data preprocessing, augmentation, and generation of synthetic data. • Design and develop backend services using Python or .NET to support OpenAI-powered solutions (or any other LLM solution) • Develop and Maintaining AI Pipelines • Work with custom datasets, utilizing techniques like chunking and embeddings, to train and fine-tune models. • Integrate Azure cognitive services (or equivalent platform services) to extend functionality and improve AI solutions • Collaborate with cross-functional teams to ensure smooth deployment and integration of AI solutions. • Ensure the robustness, efficiency, and scalability of AI systems. • Stay updated with the latest advancements in AI and machine learning technologies. • Strong foundation in machine learning, deep learning, and computer science. • Expertise in generative AI models and techniques (e.g., GANs, VAEs, Transformers). • Experience with natural language processing (NLP) and computer vision is a plus. • Ability to work independently and as part of a team. • Knowledge of advanced programming like Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. This includes the ability to implement and manipulate complex algorithms fundamental to developing generative AI models. • Knowledge of Natural language processing (NLP) for text generation projects like text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models. • Experience in Data management, including data pre-processing, augmentation, and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models. • Experience in developing and deploying AI models in production environments. • Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker and orchestration tools like Kubernetes for deploying , managing and scaling AI solutions • Should be able to bring new ideas and innovative solutions to our clients.

Signals

Skill ml-engineer

0.29

Alias ai-engineer

0.52

KRA ai-engineer

0.48

Post-classification

Centroidupdated · n=14

Alias collision log—

New-role queue—

New skills captured17

New KRA captured—

Captured for admin review

.NET primary ↔ AI Engineer pending

Keras primary ↔ AI Engineer pending

Machine Learning primary ↔ AI Engineer pending

Deep Learning primary ↔ AI Engineer pending

Generative AI primary ↔ AI Engineer pending

GANs primary ↔ AI Engineer pending

VAEs primary ↔ AI Engineer pending

Transformers primary ↔ AI Engineer pending

Natural Language Processing primary ↔ AI Engineer pending

Computer Vision ↔ AI Engineer pending

Chunking ↔ AI Engineer pending

Data Preprocessing primary ↔ AI Engineer pending

Synthetic Data primary ↔ AI Engineer pending

Text Parsing ↔ AI Engineer pending

Sentiment Analysis ↔ AI Engineer pending

GPT ↔ AI Engineer pending

AI Pipelines primary ↔ AI Engineer pending

Status: extract_from_jd_done Created: 2026-05-19T01:01:10.709542Z Updated: 2026-05-19T01:01:11.989819Z

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

Gen AI Engineer - Coimbatore

Role –Senior Gen AI Engineer

Experience : 3 Yr To 12 Yr

Location : Coimbatore

Mode of Interview - In Person

Date : 11th Oct 2025 (Saturday)

Job Description

• Collect and prepare data for training and evaluating multimodal foundation models. This may involve cleaning and processing text data or creating synthetic data.
• Develop and optimize large-scale language models like GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders)
• Work on tasks involving language modeling, text generation, understanding, and contextual comprehension.
• Regularly review and fine-tune Large Language models to ensure maximum accuracy and relevance for custom datasets.
• Build and deploy AI applications on cloud platforms – any hyperscaler Azure, GCP or AWS.
• Integrate AI models with our company's data to enhance and augment existing applications.

Role & Responsibility

Skills & Experience

• Strong foundation in machine learning, deep learning, and computer science.
• Expertise in generative AI models and techniques (e.g., GANs, VAEs, Transformers).
• Experience with natural language processing (NLP) and computer vision is a plus.
• Ability to work independently and as part of a team.
• Knowledge of advanced programming like Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. This includes the ability to implement and manipulate complex algorithms fundamental to developing generative AI models.
• Knowledge of Natural language processing (NLP) for text generation projects like text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models.
• Experience in Data management, including data pre-processing, augmentation, and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models.
• Experience in developing and deploying AI models in production environments.
• Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker and orchestration tools like Kubernetes for deploying , managing and scaling AI solutions
• Should be able to bring new ideas and innovative solutions to our clients

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)

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

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

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

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

Kubernetes Secondary 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)

Keras 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)

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

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

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

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

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

Natural Language Processing Primary No API 2 row (run stopped after API 1 or history missing)

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

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

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

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

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

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

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

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

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

AI Pipelines 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

RoleSenior Gen AI Engineer

Experience3 Yr To 12 Yr

DomainIT Services & Consulting

Location Coimbatore, India (null)

JD type pass

Show raw JSON

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  "about_company": null,
  "certifications": [],
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      },
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API 1 — extract-from-jd click to toggle

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      },
      {
        "is_primary": false,
        "queue_id": 1068,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "GPT",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 1069,
        "role_display_name": "AI Engineer",
        "role_slug": "ai-engineer",
        "skill_name": "AI Pipelines",
        "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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