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Nidhish Rao Bairineni
Mid-level AI Engineer specializing in LLMs, RAG, and MLOps
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About
Built and deployed a production RAG-based internal knowledge assistant that let analysts query company documents in natural language, using LangChain/LangGraph with Pinecone and a FastAPI service for integration. Emphasizes reliability in production through hallucination mitigation (retrieval tuning + prompt guardrails) and measurable evaluation/monitoring (accuracy, latency, task completion, hallucination rate), iterating based on user feedback.
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Key Strengths
- Built and deployed a production LLM knowledge retrieval assistant for internal analysts
- End-to-end RAG implementation (document processing, embeddings, vector DB retrieval, LLM response generation)
- Hallucination reduction via context control, retrieval tuning, and prompt guardrails
- Established evaluation metrics and production monitoring (accuracy, task completion, latency, hallucination rate)
- Pragmatic model/retrieval/prompt selection balancing cost, latency, and quality
- Effective collaboration with non-technical stakeholders to refine usability and outcomes
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