Job highlights

- 4+ years experience in Gen AI development with expertise in LLMs, RAG pipelines, vector databases, agentic AI frameworks, and ML Ops
- Build and optimize LLMs for banking use cases, develop RAG pipelines and multimodal retrieval systems, design autonomous AI workflows, implement prompt engineering and guardrails, and work with cloud AI platforms and DevOps tools

Role & responsibilities

Gen AI Developer

1. Build, fine-tune, and optimize Large Language Models (LLMs) for banking-specific use cases (credit risk, AML, KYC, audit, compliance, customer service, etc.).
2. Develop RAG pipelines, vector databases, embeddings, and multimodal retrieval systems.
3. 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.).
4. Implement prompt engineering, prompt-chaining, and guardrails for secure and compliant GenAI outputs.
5.



Work with open-source and proprietary models (OpenAI, Gemini, Llama, Claude, Mistral, Falcon, etc.).
6. Proficiency with Python, LangChain / LlamaIndex, HuggingFace, PyTorch, TensorFlow.
7. Experience with RAG pipelines, embedding models, vector databases (FAISS, Pinecone, Milvus, Chroma, OpenSearch).
8. Hands-on with agentic AI frameworks (LangGraph, Autogen, CrewAI, Haystack Agents, Swarm).
9. Experience with Azure OpenAI / AWS Bedrock / GCP Vertex AI.
10. Machine learning experience across supervised, unsupervised, time-series, and NLP.
11. Strong knowledge of ML Ops & LLM Ops (Sagemaker, Vertex AI, Azure ML, MLflow, Kubeflow).
12. Understanding of DevOps, CI/CD, Docker, Kubernetes, microservices

Preferred candidate profile 4+ years of experience

BFSI experience

📌 Gen AI Developer (Chennai)
🏢 Tata Consultancy Services
📍 Chennai