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Abhay Naik
Mid-level Data Engineer specializing in cloud-native analytics and enterprise integrations
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About
Built and productionized an LLM-powered clinical assistant at a healthcare startup, re-architecting a prototype into a robust RAG system on AWS with guardrails, citations, monitoring, and automated tests for clinical reliability. Works closely with clinicians to convert workflow feedback into evaluation criteria and iterative system improvements, and has hands-on experience debugging agentic systems in real time (including during live client demos).
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Key Strengths
- Took an LLM-powered clinical assistant from POC to production in a healthcare setting
- Designed and implemented production RAG architecture (ingestion/embeddings/retrieval/generation) with vector DB
- Built reliability and safety guardrails (schema validation, confidence thresholds, fallbacks) for clinical use
- Improved retrieval quality via data normalization, chunking, and metadata enhancements
- Implemented end-to-end observability (quality/latency/cost logging) plus monitoring and automated tests
- Strong SME collaboration loop: weekly clinician reviews, translated feedback into measurable evaluation criteria
- Real-time troubleshooting of agentic workflows by isolating failing layers and inspecting prompts/context/traces
- Handled high-pressure live demo failure by root-causing empty/irrelevant retrieval and rewriting tool-calling logic
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