Great technology is built by great teams — teams with a clear purpose, a shared vision, and the ownership to solve hard problems.
I’m an engineering leader who has built platforms, developed engineering leaders, and helped organizations navigate major technology shifts — from enterprise networking and Amazon Alexa to digital healthcare and AI-native engineering.
Today, I’m excited about the transformation AI is bringing and the opportunity to help teams embrace new possibilities, adapt, and build solutions that create lasting impact.
None of this was done alone. Every meaningful accomplishment on this page belongs to teams that trusted one another, challenged one another, and built something better together.
Looking back, the common thread across my career hasn't been healthcare, Alexa, networking, or AI. It's helping engineering organizations build platforms that become stronger, simpler, and easier to evolve over time.
I led the engineering team responsible for common speech middleware powering Alexa experiences across more than ten million devices — including Echo Show, Fire TV, Fire Tablets, and multiple device families. Supporting software at this scale reinforced lessons that still shape how I build engineering organizations today: automation is essential, observability matters more than intuition, and platform teams succeed when they make everyone else's work easier.
Healthcare is where technology becomes deeply personal. At Blink Health I helped lead multiple platform transformations spanning cloud infrastructure, CRM modernization, workforce management, communications, compliance, and AI-powered pharmacy operations. One of the most rewarding challenges was introducing agentic AI into regulated workflows. Success wasn't measured by model accuracy — it depended on earning the trust of pharmacists, operations teams, and compliance leaders through transparency, measurable outcomes, and thoughtful human oversight.
Before healthcare, I spent years building networking and security platforms where reliability wasn't simply a feature — it was the product. Working in enterprise security taught me to think in terms of resilience, observability, operational excellence, and systems that continue performing under pressure. Those lessons continue to influence every platform I help build today.
Through Nuvam.ai I'm exploring one question I hear from nearly every engineering leader: "How do we move beyond AI experiments and fundamentally change how software gets built?" Some of that work involves advising engineering organizations. Some involves building products. Most of it involves learning alongside other engineers.
Great engineering isn't measured by how indispensable you become. It's measured by how well the organization succeeds after you've stepped away.
The best AI systems don't replace engineers. They remove repetitive work so people can focus on creativity, decision making, and solving harder problems.
Technology changes continuously. The best engineers I've met remain students regardless of title or experience. That's the mindset I try to keep every day.
Outside of work I spend a surprising amount of time experimenting with AI. Some projects succeed. Some fail. Every one teaches me something.
The finished (and half-finished) versions live in the AI Lab.
The AI landscape changes weekly. Writing helps me organize my thinking and hopefully helps other engineering leaders navigate the transition.
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 thinking about platform engineering, AI adoption, leadership, healthcare technology, or simply want to compare notes, I'd love to hear from you.