Gen AI/ML (Walkin Drive)

Tata Consultancy Services; Chennai District; On-site; INR 250,000 - 550,000; Full time

Job summary

Tata Consultancy Services in Chennai is seeking an AI-focused data scientist to design, build and optimize Large Language Models for banking use cases including risk, AML, KYC, and customer service. The role involves developing retrieval systems, embeddings, and multi-agent workflows to automate complex tasks.

Candidates should have hands-on experience with Python, LangChain, PyTorch, HuggingFace, and ML Ops for scalable GenAI deployments in enterprise environments.

Qualifications

• Proficiency in building and optimizing LLMs for enterprise use cases.
• Experience with RAG pipelines, vector databases, embeddings and multimodal retrieval.
• Hands-on with agentic AI workflows and guardrails for safe GenAI outputs.

Responsibilities

• Build, fine-tune, and optimize Large Language Models for banking use cases (credit risk, AML, KYC, audit, compliance, customer service).
• Develop RAG pipelines, vector databases, embeddings, and multimodal retrieval systems.
• Design and integrate agentic AI workflows and multi-agent orchestration for complex banking tasks.
• Implement prompt engineering, prompt-chaining, and guardrails for safe GenAI outputs.

Skills

Gen AI

AI Governance

AI Data Scientist

Job description

Skill : Gen AI, AI Governance, AI Data Scientist

Exp : 4 - 15 Yrs

Mode of Interview : Walkin Drive or Face to face Interview

Location :

TCS -Magnum Block and Chennai One IT SEZ Phase-2, 200 Feet Radial Road, MCN Nagar Extension, Thoraipakkam, Chennai - 600097

Job Description :

• Build, fine-tune, and optimize Large Language Models (LLMs) for banking-specific use cases (credit risk, AML, KYC, audit, compliance, customer service, etc.)
• Develop RAG pipelines, vector databases, embeddings, and multimodal retrieval systems.
• Design and integrate agentic AI workflows, autonomous agents, and multi-agent orchestration for complex banking tasks (case investigation, decision reasoning, trade surveillance alerts, credit assessment, etc.)
• Implement prompt engineering, prompt-chaining, and guardrails for safe and compliant GenAI outputs.
• Work with open-source and proprietary models (OpenAI, Gemini, Llama, Claude, Mistral, Falcon, etc.)
• Proficiency with Python, LangChain / LlamaIndex, HuggingFace, PyTorch, Tensor Flow.
• Experience with RAG pipelines, embedding models, vector databases (FAISS, Pinecone, Milvus, Chroma, OpenSearch)
• Hands-on with agentic AI frameworks (LangGraph, Autogen, CrewAI, Haystack Agents,Swarm)
• Experience with Azure OpenAI / AWS Bedrock / GCP Vertex AI
• Machine learning experience across supervised, unsupervised, time-series,and NLP
• Strong knowledge of ML Ops & LLM Ops (Sagemaker, Vertex AI, Azure ML, MLflow,Kubeflow)
• Understanding of DevOps, CI/CD, Docker, Kubernetes, microservices