Risk Modeling Solutions - Full-stack GenAI - Assistant Vice President
Citi (company site, opens in a new tab)6+ yrsBengaluruOn-siteDirect career pageEst. 30–50 LPA
Posted 1d ago
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Job description
Structured overview of role & requirements
About This Role
- Lead design and implementation of complex multi-agent AI workflows for advanced reasoning and autonomous execution within risk management.
- Develop end-to-end AI solutions translating complex risk domain problems into scalable technical implementations, including backend API and microservice development.
- Architect and optimize Retrieval-Augmented Generation (RAG) pipelines and containerized AI deployments with CI/CD, observability, and evaluation frameworks to enhance model quality and operational efficiency.
Minimum Requirements
- 6+ years of combined software development and data science/machine learning experience.
- Expert-level Python skills with proven backend services and API development experience (FastAPI preferred).
- Hands-on expertise designing and building multi-agent AI frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen) and RAG systems integrated with vector databases (e.g., Pinecone).
- Proven experience deploying containerized AI systems on major cloud platforms (AWS, Azure, GCP) and applying MLOps best practices including CI/CD and observability.
Ideal Candidate Profile
- Experienced in designing and leading advanced AI workflows with multi-agent frameworks tailored to risk modeling environments.
- Strong background in AI risk, safety, governance in regulated industries like financial services.
- Familiarity with AI observability tools (e.g., Langfuse) and cloud AI services (e.g., AWS Bedrock, Azure AI Foundry) to drive robust evaluation and deployment.