I'm the founding engineer at MakeTimeFlow, building the company's AI agent systems in close collaboration with the CEO: a voice-enabled coaching agent (Claude API + ElevenLabs real-time speech), the integration architecture connecting it to users' calendars and workflows, and the AI-native development workflows the engineering team runs on. I work across the full product lifecycle, from customer research and product strategy through architecture and deployment.
Before MakeTimeFlow, I led engineering on two competitively funded NSF research platforms ($1.2M+ combined) at the University of Houston. One supported emergency food distribution logistics for the Houston Food Bank; the other targeted counterfeit pharmaceutical vendor prediction. I owned the full AWS stack, microservices architecture, and data pipeline reliability. Before that, I built deep learning training pipelines at UChicago Radiology, where I led a small team developing U-Net segmentation models for detecting ablation zones during histotripsy treatment of renal tumors and improved baseline performance by 240%.
My path into engineering started in music. I studied audio design at Columbia College Chicago and wrote and produced music that's accumulated over two million views on YouTube. Studio work trains the same instincts engineering demands: signal versus noise, iteration under constraints, and knowing when something is done versus when you're just noodling. Those instincts carried over when I earned my M.A.S. in Computer Science at Illinois Institute of Technology.
The power of these systems is growing fast, and how we build them matters as much as what we build. I care about building systems that hold up under real-world pressure, and I think the best engineering happens when technical rigor meets curiosity and a real connection to the people using the thing.