Applied AI Architecture | Multi-Agent Systems | Cloud and SI Delivery
The gap between AI strategy and production systems is where most projects fail. I work in that gap.
I started as a hands-on software engineer who loved turning messy problems into clean, reliable code. That curiosity grew into a passion for systems that don't just work, but unlock bigger business outcomes the kind you can measure in faster delivery, happier users, and fewer late-night pages.
Along the way I moved from shipping features to shaping how teams build. I learned to sketch target states, draw domain boundaries, and guide teams from monoliths to modern architecture: DDD, API-first, event-driven — so change is safer and value lands in small, steady increments.
Today my focus is applied AI in enterprise environments. Designing systems that work in the real world, not just in a demo. Real users, real constraints, hard trade-offs. I write the architecture and stay in the delivery until it ships.
I build AI systems that go into production and stay there. Multi-agent architectures, safety controls, evaluation pipelines, and the delivery work that bridges the gap between a working prototype and something thousands of people rely on.
Good AI strategy is not a slide deck. It is a set of decisions that engineering teams can actually execute. I work with senior stakeholders to define where an organization is going with AI, then stay involved long enough to make sure the architecture reflects it.
Good AI architecture starts before the models. Domain-driven design, API-first patterns, and clean system boundaries are what make an AI system extensible, observable, and safe to evolve. I have been building that foundation for years.
I do not hand off to a delivery team. I lead from inside it: mentoring engineers, running architecture reviews, and making sure the patterns we agreed on at the whiteboard actually show up in the code.
I started as a software engineer and never really stopped. The architecture came later but the builder instinct underneath it is the same. I know what a design decision costs the engineer implementing it.
Medium / Slalom Technology · Feb 2023
Medium / Slalom Technology · Apr 2018
Medium / Slalom Technology · Jan 2021
I build things outside of work because I genuinely enjoy it. AI experiments, SaaS prototypes, side projects that sharpen my thinking. I also write and mentor, two things that force you to articulate what you actually know versus what you think you know.