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Naim San
Senior AI/ML Engineer specializing in Python, RAG systems, and LLM fine-tuning
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About
Built and owned an end-to-end RAG-based AI support platform at Mechanize (FastAPI/LangChain/Pinecone/React) with rigorous evals and guardrails, driving 45% fewer support tickets and ~$280K annual savings. Also led a high-risk legacy modernization at Argo AI, incrementally extracting a monolithic Django backend using Strangler Fig + feature flags while supporting 10K+ concurrent users.
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Key Strengths
- Owned and shipped end-to-end RAG support platform (frontend, backend, data, infra) with measurable impact (45% fewer tickets, ~$280K annual savings, 80%+ self-serve resolution)
- Strong production evaluation/monitoring approach (offline labeled evals + live fallback-rate canary + confidence distribution dashboards)
- Pragmatic LLM guardrails and prompt design focused on reducing harmful wrong answers (confidence threshold + 'say you don’t know')
- Legacy modernization leadership using Strangler Fig + feature flags to migrate high-traffic endpoints without regressions for 10K+ concurrent users
- High-leverage use of AI dev tools to accelerate large refactors (Pandas→Polars across 40+ files in ~2 days) while maintaining review/testing discipline
- Effective cross-functional discovery and roadmap shaping with exec stakeholders (CPO/CTO), including scope control and phased delivery
- Able to run multiple parallel workstreams with minimal oversight and ship iteratively with tight user feedback loops
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