I believe the best AI is the kind you don't even notice. As an AI engineer specializing in healthcare innovation, I build systems that transform complex data into clear, actionable insights—whether that's parsing years of medical records into personalized health recommendations or tracking real-time patterns in streaming data.

Currently, I'm crafting next-generation healthcare experiences at N1 Healthcare, where we're pioneering truly personalized medicine. Imagine uploading your entire medical history and receiving a comprehensive report that not only explains your health in plain English but visualizes trends you never knew existed. That's the kind of invisible magic I create—complex AI orchestration behind the scenes, simple clarity for the user.

My technical playground includes Python, LangChain, vector databases, and the full MLOps stack. Recently, I architected a real-time traffic violation detection system using Kafka streams and MongoDB—turning raw camera data into instant insights. I thrive on challenges like optimizing GPU inference, building RAG workflows that actually understand context, and ensuring every model I deploy is fast, cost-efficient, and production-ready.

What sets me apart? I'm constantly exploring the bleeding edge of AI through GitHub repos, research papers, and hands-on experimentation. I believe in taking calculated risks—sometimes stepping back to leap forward with innovative solutions that others might overlook. My toolkit evolves weekly because in AI, standing still means falling behind.

When I'm not fine-tuning models or containerizing services for Google Cloud, you'll find me building my next side project, dabbling with new AI tools, or training Jiu Jitsu with my friends. Each pursuit teaches me something new about problem-solving that I bring back to my code.