GenAI Data scientist

Tata Consultancy Services; Chennai District; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Tata Consultancy Services in Chennai is seeking a hands-on GenAI/LLM specialist to craft GenAI applications, AI agents, and RAG-based workflows. You will work with Python, LangChain, LangGraph, and React frontends while implementing guardrails and scalable ML pipelines in a cloud-enabled environment.

Association with cross-functional teams is expected to translate business problems into analytical tasks and deliver robust, secure AI solutions aligned with enterprise needs.

Qualifications

• Hands-on experience with GenAI, Gemini or Open source LLMs and develop GenAI applications for Code Translation, Text Extraction, Summarisation and SDLC Optimization.
• Hands-on Experience with AI Agents, Chat bots, RAG, and vector databases (PG vector / chroma DB).
• Experience with GenAI performance evaluation tools like Pegasus, Ragas, DeepEval.
• Create Conversational Interfaces with React JS and deploy AI agents using LangGraph and ADK, A2A, MCP.
• Strong programming skills in Python (LangChain/LangGraph) and TypeScript (preferable).
• Understanding of LLMs, prompt engineering, and graph-based workflows.
• Knowledge of input and output guardrails, hallucination, PII filtering, bias.
• Security best practices, spikes and DDoS mitigation.
• Knowledge of API Gateways and Istio.
• Hands-on API Development and Microservices architecture.

Skills

GenAI

LLM

AI Agents

RAG

Python

TypeScript

LangChain

LangGraph

LangSmith

React JS

Tools

API Gateways

Istio

LangChain

LangGraph

LangSmith

ReactJS

ADK

A2A

Job description

Skills: GenAI, LLM, AI Agents, RAG, Python

Preferred candidate profile :

• Hands-on experience with GenAI, Gemini or Open source LLMs and develop GenAI applications for Code Translation, Text Extraction, Summarisation and SDLC Optimization etc.
• Hands-on Experience with AI Agents, Chat bots, RAG (Retrieval-Augmented Generation), and vector databases. ( PG vector / croma DB )
• Hands-on Experience with GenAI Performance Evaluation tools like Pegasus, Ragas, DeepEval
• Create Conversational Interface with React JS or other Frontend components, Develop and deploy AI agents using LangGraph and ADK, A2A, MCP
• Strong programming skills in Python (experience with LangChain/LangGraph / LangSmith frameworks) and TypeScript ( preferable )
• Solid understanding of LLMs, prompt engineering, and graph-based workflows.
• Knowledge and implementation of Input and Output guardrails in addressing Hallucination, PII filtering, HAP and Bias etc.
• Implemented security best practices, Experience to address spikes and Denial of wallet attacks, DDoS attack and other Spike arrest strategies
• Knowledge of API Gateways and ISTIO , ability to Diagnose and intercept failures in End to End communication
• Hands-on Experience with API Development and Microservices architecture

Desirable skills/knowledge/experience: (As applicable)

• Strong experience applying machine learning, statistical modelling, and predictive analytics to realworld business problems.
• Collaborate with cross-functional teams to ability to resolve end to end connectivity and Data Integrations
• Experience working with large, complex datasets, including data cleaning, feature engineering, and exploratory data analysis.
• Familiarity with LLMs, NLP techniques, and GenAI frameworks, including embeddings, prompt engineering, or finetuning.
• Experience building endtoend ML pipelines, including model validation, optimisation, deployment, and monitoring.
• Understanding of MLOps practices, including model versioning, model registries, CI/CD for ML, and automated training/inference workflows.
• Ability to translate business problems into analytical tasks and communicate insights in a clear, concise manner to technical and nontechnical audiences.
• Knowledge of data governance, including data quality, lineage, ethics, privacy considerations, and responsible AI principles.
• Comfort working with cloud platforms (GCP preferred) for model training, deployment, and scalable compute.
• A growthoriented mindset with enthusiasm for exploring new algorithms, tools, and emerging AI/ML techniques.