Role Purpose :

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 modernizing Retail Credit Risk and Operational Risk across the bank.

Key Responsibilities :

- 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 elite 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.

Required Skillset :

- Demonstrated expertise in designing and implementing Generative AI models and LLM frameworks within the financial services or retail banking domain.

- Strong command over SQL and data engineering principles to manage large-scale, complex datasets in a high-pressure banking environment.

- Proven ability to lead and manage high-performing technical teams, with a focus on project delivery and stakeholder management.