I lead AI strategy and execution — growing engineering and ML organizations, turning ambiguous problems into clear roadmaps, and shipping products that people rely on every day.
Connect on LinkedInPlenty of teams experiment with AI. Far fewer ship it. I've spent my career closing that gap — taking AI products from early idea to systems in production, used at scale, delivering outcomes a business can measure.
As an AI and ML leader, I own the full lifecycle: spotting the use cases worth betting on, setting the technical direction, building the teams to execute, and seeing solutions through deployment and beyond. I've grown small engineering groups into large, multi-disciplinary AI organizations — and kept the culture of craft and ownership intact while doing it.
Setting the vision for where AI creates real value, and translating ambiguous business problems into roadmaps teams can actually execute.
Growing high-performance engineering and ML organizations — hiring for craft, developing people toward ownership, and protecting the conditions where deep technical work thrives.
Driving generative AI capabilities from concept to production — secure, enterprise-grade systems designed to scale and built to last.
Working alongside leaders across product, engineering, marketing, and customer teams to align AI investment with measurable business outcomes.
Bringing discipline to AI delivery — removing blockers, compressing feedback loops, and shipping fast without trading away quality.
The best technology leaders don't just set direction — they stay close to the work.
I still code, experiment, and get into the details, because strategy without ground-level execution is just theory. That connection between vision and delivery is what I protect most in how I lead.
Always open to conversations on AI leadership, scaling teams, and what it takes to build AI products that make it to production.
Connect on LinkedIn