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sathwik kuchana
Mid-level AI Engineer specializing in Generative AI, LLMs, and RAG on AWS
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Built and deployed an LLM-powered clinical decision support and risk monitoring platform for mental health at Valuai.io, emphasizing low-latency, evidence-grounded responses and crisis-safe behavior with clinician escalation. Strong production agent-orchestration background (LangChain/CrewAI) plus rigorous evaluation (clinician-in-the-loop + evaluator agent) and large-scale synthetic testing; also applied multi-agent workflows to document verification and fraud detection during an AI internship at Nixacom.
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Key Strengths
- Deployed safety-aware clinical LLM platform for mental health workflows in production
- Reduced LLM workflow latency 85% (8s to 1.2s) via re-architecture and Redis caching
- Built evidence-grounded RAG over PubMed + APA guidelines to reduce hallucinations and token usage
- Designed crisis detection + clinician escalation workflows for high-risk conversations
- Built scalable evaluation approach combining clinician scoring with automated evaluator agent
- Created large-scale test harness with 20,000+ synthetic patient profiles and regression checks
- Production-focused orchestration across routing, retrieval, guardrails, and downstream actions (LangChain/CrewAI)
Reference Highlights
- Led projects end-to-end from scratch (design through deployment)
- Strong leadership/ownership
- Built and deployed multi-agent architecture
- Focused on factual accuracy in healthcare AI (avoided factual inaccuracy)
- Effective communicator with non-technical stakeholders
- Able to work directly with clinicians and operations teams
- Explains model performance clearly to clinicians
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