VP Risk GenAI Led Transformation

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Key Responsibilities:

Lead the strategy, development, and deployment of Generative AI (LLMs) and advanced AI models within the Risk Data Management horizontal. You will manage data engineers and high-potential IIT freshers to build scalable AI assets, focusing heavily on modernizingÂ Retail Credit RiskÂ andÂ Operational RiskÂ across the bank.
GenAI Strategy: Identify, blueprint, and execute Large Language Model (LLM) use cases like automated credit appraisal memo (CAM) generation, multi-source financial analysis, and AI-powered operational risk loss incident tagging.
Horizontal Execution: Act as the AI consultant for all 7 risk verticals, with an immediate focus on Retail Credit (automated underwriting, early warnings) and Operational Risk (anomaly detection, control testing automation).
Team Leadership: Manage and mentor a team of Risk Data Engineers and eliteÂ IIT freshers, bridging academic AI knowledge with practical banking applications.
Pipeline Collaboration: Work closely with the Risk Data Management infrastructure to ingest, clean, and structure unstructured bank data for LLM fine-tuning and Retrieval-Augmented Generation (RAG) pipelines.
RBI Compliance & Safety: Mitigate risks specific to GenAI, including hallucination management, data privacy (PII masking), model bias, and alignment with Reserve Bank of India (RBI) AI governance norms.

Role Proficiencies:

Total Experience: 8 to 12 years in analytical or technology transformation roles.
GenAI/LLM Focus: Minimum 2+ years of hands-on experience building, fine-tuning, or deploying LLM frameworks (e.g., using LangChain, LlamaIndex, vector databases) in a corporate environment.
Domain Expertise: Strong exposure to financial services, preferably with a deep conceptual grasp of Retail Credit underwriting or Operational Risk frameworks.
People Management: Prior experience managing young, highly analytical engineering talent (like IIT/NIT grads) and aligning them with business goals.
GenAI Ecosystem: Python, PyTorch, Hugging Face, OpenAI API/Open-Source LLMs (Llama, Mistral), Vector DBs (Pinecone, Chroma, Milvus).
â€¢ Data Engineering: SQL, Spark, cloud data warehouses (Snowflake, Databricks), and orchestration tools.

Experience:
8 - 12 Years
Salary:
50 LPA - 55 LPA
Diversity Candidate:
Yes
Location:
Mumbai
Address:
Worli
Primary Skills:
ython, PyTorch, Hugging Face, OpenAI API/Open-Source LLMs (Llama, Mistral), Vector DBs (Pinecone, Chroma, Milvus)
Industry:
BFSI Fintech & Financial Services
Job Type:
Full time
Degree:
graduate