What You'll Do - Design and implement stateful multi-agent networks and/or workflows using LangGraph and/or LangChain. - Build and optimise end-to-end RAG pipelines, focusing on high-precision retrieval, semantic search, and the integration of diverse data sources (vector DB, graph DB, RDBMS, etc). - Architect and implement multi-layered guardrails to ensure agent actions remain within business scope, enterprise safety and policy boundaries. - Build and maintain high-performance AI microservices, ensuring they are optimised for OCI-compliant environments. - Use of LLM evaluation frameworks to quantitatively measure agent performance. - Partner with software teams to define data contracts and integrate information flow from AI layer to software backend and frontend.
Technical Requirements - Expert-level proficiency in Python, specifically for asynchronous AI applications. - Mastery of LangGraph and LangChain for building production-grade, stateful systems with human-in-the-loop verif...