Found Description
Exp : 7- 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 system
s.
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 outp
uts.
Work with open-source and proprietary models (OpenAI, Gemini, Llama, Claude, Mistral, Falcon, e
tc.).Proficiency with Python, LangChain / LlamaIndex, HuggingFace, PyTorch, Tensor
Flow.
Experience with RAG pipelines, embedding models, vector databases (FAISS, Pinecone, Milvus, Chroma, OpenSe
arch).
Hands-on with agentic AI frameworks (LangGrap...
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 system
s.
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 outp
uts.
Work with open-source and proprietary models (OpenAI, Gemini, Llama, Claude, Mistral, Falcon, e
tc.).Proficiency with Python, LangChain / LlamaIndex, HuggingFace, PyTorch, Tensor
Flow.
Experience with RAG pipelines, embedding models, vector databases (FAISS, Pinecone, Milvus, Chroma, OpenSe
arch).
Hands-on with agentic AI frameworks (LangGrap...