Key Responsibilities

Agent Development & Architecture:

Build agentic workflows using Lang Chain/Lang Graph and similar frameworks.

- Develop autonomous agents for data validation, reporting, document processing, and domain workflows

Deploy scalable, resilient agent pipelines with monitoring and evaluation

Gen AI Application Engineering

Develop Gen AI applications using models like GPT, Gemini, and LLa M

Implement RAG, vector search, prompt orchestration, and model evaluation

Partner with data scientists to productionize POCs

Data & Platform Engineering

Build distributed data pipelines (Python, Py Spark)

Develop APIs, SDKs, and integration layers for AI-powered applications

Optimize systems for performance and scalability across cloud/hybrid environments.

MLOps / LLMOps

Contribute to CI/CD workflows for AI models-deployment, testing, monitoring

Implement governance, guardrails, and reusable Gen AI frameworks.

Collaboration & Stakeholder Engagement

Work with analytics, product, and engineering teams to define and deliver AI solutions

Participate in architecture reviews and iterative development cycles

Support knowledge sharing and internal Gen AI capability building.

Key Requirements





8-12 years of experience in AI/ML engineering, data science, or software engineering, with atleast 2 years focused on Gen AI

Strong programming expertise in Python, distributed computing using Py Spark, and API development

Hands on experience with LLM frameworks (Lang Chain, Lang Graph, Transformers, Open AI/Vertex/Bedrock SDKs)

Experience developing AI agents, retrieval pipelines, tool calling structures, or autonomous task orchestration

Solid understanding of Gen AI concepts: prompting, embeddings, RAG, evaluation metrics, hallucination identification, model selection, fine tuning, context engineering

Experience with cloud platforms (Azure/AWS/GCP), containerization (Docker), and CI/CD pipelines for ML/AI

Strong problem solving, system design thinking, and ability to translate business needs into scalable AI solutions

Excellent verbal, written communication and presentation skills. Valuable to Have

Experience in workflow automation and building reusable AI components

Background in analytics, statistical models, or enterprise data products

Experience with MLOps / LLMOps tooling

📌 Data Scientist (Chennai)
🏢 Dun u0026 Bradstreet India
📍 Chennai