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naveena musku
Senior AI/ML Engineer specializing in Agentic AI and LLM automation
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Backend engineer focused on productionizing LLM systems: built a FastAPI-based RAG and multi-agent automation platform deployed with Docker/Kubernetes, prioritizing safe execution and reduced hallucinations. Experienced in refactoring monolithic ML services with feature-flagged incremental rollouts, and implementing JWT/RBAC plus row-level security (e.g., Supabase) for secure, scalable APIs.
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Key Strengths
- Designed and deployed production LLM RAG + multi-agent backend with reliability/scalability/safe execution focus
- Pragmatic architectural tradeoff decisions (accepted higher latency to reduce hallucinations and improve grounding)
- Production-grade API engineering in FastAPI (clean contracts, stateless design, logging, timeouts/retries, containerized scaling)
- Low-risk migrations/refactors using side-by-side deployments and feature-flagged incremental traffic shifts
- Security implemented at both API and data layers (JWT auth, RBAC, row-level security)
- Proactively identified LLM workflow failure modes via logs and added validation/guardrails to reduce error rates and improve graceful failure
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