I am a Lead AI Engineer with 5+ years of experience specializing in the design and deployment of production-scale Generative AI and Machine Learning systems. My career has been defined by a transition from core ML and predictive modeling at Microsoft and GE to architecting cutting-edge Agentic RAG platforms in the startup ecosystem. I have a proven track record of shipping high-impact AI products, most recently leading the development of a multi-tenant vector search system using Postgres (pgvector) that automated 80% of support workflows and significantly reduced system hallucinations. My technical depth spans the entire GenAI lifecycle, from hybrid retrieval strategies and reranking layers to building robust LLM guardrails that ensure groundedness and traceability. Beyond the code, I focus on the strategic side of AI—defining evaluation metrics, designing A/B tests, and mentoring engineering teams to bridge the gap between complex research and measurable business outcomes. Whether I am optimizing distributed data pipelines in Spark or engineering structured JSON responses for downstream integrations, my goal is always to build AI that is reliable, scalable, and enterprise-ready