Define and maintain the enterprise AI platform architecture, technology roadmap and reference architecture for the Central AI Kitchen (CAK) or equivalent AI platforms.
Architect production-grade RAG workflows on cloud resources (e.g. AWS, GCP) using reliable tools (e.g. LangGraph / LlamaIndex). Build agents that can plan multi-step financial tasks
Explore and apply advanced Generative AI techniques, including agentic AI frameworks (e.g. Azure AI SDK, Strands, LangChain, LangGraph), retrieval-based methods, and prompt engineering for healthcare use cases
Design and implement multi-step agentic AI workflows: agent orchestration (single-agent and multi-agent coordination), tool-calling architectures, memory and state management, and planning and reasoning loops using frameworks such as LangGraph, AutoGen, or custom orchestration.
Design and build data architectures specifically optimised for AI agent consumption: structured data stores accessible via tool-calling APIs, vector knowledge bases for semantic retrieval, graph databases for relationship-based reasoning, and hybrid retrieval systems that combine keyword, semantic, and structured query approaches.