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 an...
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