Founder-Level Ownership
I co-founded Dauber and helped build construction-hauling software through ambiguity, customer pressure, engineering tradeoffs, team leadership, and acquisition-level scrutiny.
Software Engineer & Systems Architect
Founder, engineering leader, and hands-on builder focused on applied AI for real business, where domain context, verification, and trust matter.
Most of my best work has been in domains where the problem is not clean at the edges.
Dauber, the construction-hauling software company I co-founded and later sold, was built in one of those domains. We served an industry where dispatch, drivers, jobs, customers, billing, and trust had to line up in the real world, while much of the work still ran through phone calls, paper tickets, spreadsheets, and “where is my truck?” moments. Dauber moved those workflows into software that made them visible, trackable, trustworthy, and easier to operate.
That experience shaped the architecture I still value: clear domain models, CQRS when it fits, event sourcing when history matters, durable workflows, practical integrations, and infrastructure that is boring in the best way. At Dauber, that meant C#/.NET, Azure DocumentDB, Table Storage, event messaging, web and mobile apps, and connecting software to real operations.
I’m interested in applied AI for the same reason. The useful part is not the demo; it is knowing where AI belongs in a workflow, what context it needs, how people verify its output, and how responsibility stays clear when mistakes have a cost.
Successful outcomes take a common shape: understand the domain, model the work, preserve the facts, and build systems people can trust.
My experience has centered on turning ambiguous operations into dependable products: clarifying workflows, modeling the state that actually matters, and shipping systems that hold up when users rely on them daily.
I co-founded Dauber and helped build construction-hauling software through ambiguity, customer pressure, engineering tradeoffs, team leadership, and acquisition-level scrutiny.
I design around the business: clear boundaries, durable workflows, useful history, practical integrations, and state that teams can reason about.
I’m focused on where AI belongs in real workflows, what context it needs, how people verify its output, and how responsibility stays clear.
I work across architecture and implementation, including .NET/C#, Angular, Azure, SQL, document storage, messaging, mobile apps, pipelines, and product decisions.
A runnable .NET reference project for developers and architects who want to see how RAG behaves inside an application with clear domain boundaries. It processes local files, applies access rules, and lets you ask questions that return secure, grounded answers.
I’m interested in work where domain complexity, product judgment, and durable engineering all matter.