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 LangG...