I'm an engineer at heart who somehow ended up leading teams — and I've been fortunate to spend two decades building things in places where the work really matters: healthcare, smart devices, and enterprise security.
None of what's on this page was done alone. The best work of my career has always come from great teams — this is simply my small record of what we built together, and what I learned along the way.
Less a highlight reel, more a ledger — the projects and teams that shaped me.
I managed the common speech middleware that enabled the Alexa experience across more than 10 million devices and over a dozen device categories — Echo Show, Fire TV Stick, Fire TV Cube, Fire Tablets, and more. It was a great experience in appreciating the value of building test suites and automation, and in learning to diagnose voice-interaction issues across such a diverse device fleet.
Made possible by some of the most rigorous engineers I've ever worked alongside.
We reimagined pharmacy operations under strict compliance constraints — incrementally improving automation, combining agentic AI with traditional automation to reach over 50% touchless operations. The hard part wasn't the AI; it was earning the trust of pharmacists and regulators one careful step at a time.
Credit belongs to a team that cared as much about patients as about code.
I contributed to high-stakes platform architecture where reliability and auditability weren't features — they were the product. This is where I learned that boring, predictable systems are often the bravest thing you can build.
These days, through Nuvam, I try to give back what I've learned — helping engineering organizations work through accumulated friction in their processes, architecture, and AI adoption. Mostly, I listen first.
Every system I'm proud of was really a team I was proud of. My job is mostly to remove obstacles and get out of the way.
Show up, help build the foundations that are missing, and leave the team structurally stronger than I found it.
AI is changing our craft faster than anything I've seen. I try to stay a student of it — and share notes as I go. My AI-Lab is where that tinkering lives.
A practical framework for engineering leaders navigating the shift to AI-augmented organizations — strategy, team structure, and delivery.
Read on LinkedIn → Deep DiveA look at LLM token economics for engineering leaders — costs, optimization strategies, and real-world budget implications.
Read on LinkedIn →Thoughts brewing on agentic AI, platform architecture, and engineering org design.
Follow along on LinkedInWhether you're wrestling with an engineering org problem, exploring AI adoption, or just want to compare notes — my inbox is open. I try to reply to everyone.