Data & AI Engineer with 13+ years across enterprise data platforms and production GenAI systems - Healthcare, BFSI, Supply Chain, Telecom. I build production RAG platforms on Azure OpenAI, agentic multi-agent systems (LangGraph, MCP), multimodal document intelligence, and NL-to-SQL, alongside large-scale data pipelines on Azure (Databricks, Data Factory, Synapse, ADLS), Spark/Scala, and Kafka.
💬 Ask me about: RAG architecture, hybrid retrieval & reranking, agentic multi-agent systems, MCP, multimodal document intelligence, NL-to-SQL safety, Azure data platforms
- hybrid-rag-engine - a hybrid retrieval RAG platform: pgvector cosine search + full-text search, combined with Reciprocal Rank Fusion, cross-encoder reranking, and citation-grounded streaming generation
- agentic-fact-verifier - a LangGraph multi-agent system that fact-checks claims using a ReAct search agent, fuzzy entity matching, statistical trust scoring, and an MCP tool server
- nl2sql-guardrails - natural-language-to-SQL, grounded with RAG and locked down with multi-layer SQL safety validation, caching, and per-datasource concurrency control
- multimodal-doc-auditor - parallel, fault-tolerant document compliance auditing using GPT-4o Vision plus OCR cross-verification
- multi-agent-support-router - a LangGraph controller/specialist chatbot that escalates incomplete answers and streams its reasoning live over SSE
- MIT IDSS Data Science & Machine Learning Program - MIT (In Progress, 2026)
- Executive PG Programme in Machine Learning & Artificial Intelligence - IIIT Bangalore (2021-2022)
- Machine Learning Engineer Nanodegree - Udacity (2020)
- B.Tech. Computer Science - Mody University of Science & Technology (2008-2012)
