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Vinay Chandra Vudharam
Mid-level AI Engineer specializing in GenAI, agentic workflows, and RAG systems
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About
Built a production multi-agent RAG assistant using LangChain/LangGraph with OpenAI embeddings and FAISS, focusing on retrieval quality and latency (Redis caching, parallel retrieval, precomputed embeddings). Experienced orchestrating ETL/ML pipelines with Airflow and Databricks Workflows, and has delivered an AI assistant for business ops to extract insights from policy/compliance documents through close non-technical stakeholder collaboration.
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Key Strengths
- Built and deployed a multi-agent RAG system (planner/retriever/reasoning) using LangChain/LangGraph + FAISS
- Improved retrieval quality through chunk-size, embedding, and retrieval-strategy tuning
- Reduced latency via Redis caching, parallelized retrieval, and precomputed embeddings
- Structured reliability approach: modular agent roles, unit tests for retrieval/prompting, edge-case evaluation, metric-driven iteration
- Strong stakeholder collaboration: translated business needs into a usable RAG assistant and iterated via prototype testing feedback
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