Gen AI

Job description

Gen AI Exp

3 – 15 yrs

• 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, TensorFlow.
• 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, V ertex AI, Azure ML, MLflow, Kubeflow).
• Understanding of DevOps, CI/CD, Docker, Kubernetes, microservices</p

Qualifications

Undergraduate