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Tata Consultancy Services
Gen AI/ML
Tata Consultancy Services
Chennai•On-site•Salary•7-10 Yrs•2 days ago
Job description
Gen AI/MLLLMsRAGAgentic AIPrompt EngineeringNLPMLOpsAzureTensorFlowPyTorch
Overview
Build, fine-tune, and optimize Large Language Models (LLMs) for banking-specific use cases including credit risk, AML, KYC, audit, compliance, and customer service. Develop RAG pipelines, vector databases, embeddings, and multimodal retrieval systems. Design and integrate agentic AI workflows. Implement prompt engineering techniques and working with open-source and proprietary models.
Responsibilities
- Build, fine-tune, and optimize Large Language Models (LLMs) for banking-specific use cases
- 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
- 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.)
- 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
Qualifications
- 7-15 years of experience
- 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
Benefits
- Competitive, family friendly total rewards package