As an AI Engineer with 3+ years of professional experience spanning software engineering and applied AI, I focus on building production-grade systems powered by Large Language Models, Retrieval-Augmented Generation, and Agentic AI. My work centers on the often-overlooked middle layer — the orchestration, prompt engineering, vector retrieval, and infrastructure that turn raw model capabilities into reliable, scalable products.

My path into AI started in traditional software engineering. I built backend systems, optimized SQL queries, and automated cloud deployments at AJR Info Systems in India before pursuing my Master's in Computer Science at the University of Texas at Arlington. Internships at Growith and an AI & Data Analyst role at UTA pulled me deeper into intelligent systems, and I eventually joined TechMentee as an AI Engineer — where I now design end-to-end LLM architectures and AI-driven workflows.

Outside of building, I write about AI engineering on Medium, follow emerging research in agentic systems and LLM orchestration closely, and explore how new model capabilities can be turned into real products. I'm a strong believer that the most valuable AI isn't the most sophisticated — it's the kind that actually ships, scales, and solves a real problem someone has.