Engineering leader with 20+ years architecting enterprise Azure infrastructure. I designed and led the platform behind a $150M global managed-services business. I still ship the code.
I architect and lead the platforms enterprises depend on. At Rackspace I built and ran the core Azure platform behind a $150M global managed-services business. It was PostgreSQL-backed, with Cosmos DB audit logging and an event-driven backbone of Service Bus, Event Hubs, and Azure Functions, serving 36,000+ tenants and 5,000 subscriptions across 13 global sites.
The outcomes are what I'm measured on. I refactored that platform from $56K to $9K per month, an 84% cut while increasing capacity, drove mean-time-to-resolution from five hours to fifteen minutes with AIOps, cut deployments from 48 minutes to 6, and passed every annual Azure Expert MSP audit with zero findings. I grew the team from myself to eight engineers and championed AI adoption across the org.
I lead by building. I architect the systems my teams run on and stay close to the code, so my technical decisions hold up and my team trusts them. That work runs from the enterprise identity practice I stood up on Entra ID and federation, through the Zero Trust security model, to the agentic systems I build now: MCP services, custom agent coding skills, and Borg, my open-source agent-memory engine.
My AI work is real engineering, not a list of tools I've tried. I built the agentic surface of a production platform, led AI adoption across my team, and maintain open-source AI infrastructure with published benchmarks. The work below is grouped by where it happened: production, leadership, and open source.
Built the platform's programmatic and agentic layer: REST APIs, Model Context Protocol services, agent frameworks, and custom agent coding skills, with the documentation to make it usable inside and out.
Integrated an AIOps framework using machine-learning event correlation that cut mean-time-to-resolution from five hours to fifteen minutes across a multi-tenant estate.
Served as my team's AI champion and trainer, running demos and proofs of concept, upskilling engineers, and integrating AI-assisted workflows into production engineering practice.
Built an open-source, Postgres-native memory system giving AI coding agents organization-level memory. Benchmarked at 91.3% retrieval precision, 12.7 points over vector RAG. See details ↓
I build with agents daily, writing custom agent coding skills and MCP integrations that extend what they can do and speed up delivery across the stack.
I design how agents fit into real engineering systems, using namespace isolation, token-budgeted context, and bitemporal fact supersession so AI strengthens the platform rather than adding risk to it.
Held engineering accountability for the core Azure platform underpinning a $150M managed-services business, built on PostgreSQL with Cosmos DB audit logging and an event-driven backbone of Service Bus, Event Hubs, and Azure Functions.
Built out the Identity and Access Management practice on Azure AD, ADFS, and Microsoft Identity Manager, delivering single sign-on and federated identity at scale across cloud and on-premises.
Local practice lead for the Austin business unit, owning delivery across Azure, Office 365, and federation, managing the full project lifecycle from sales to closure.
Lead architect for enterprise virtualization and identity, building Active Directory and high-availability infrastructure at 99.99% uptime. This was the foundation for everything since.
The team I built is the part of this work I'm proudest of. I care about it more than any platform I've shipped.
I grew my engineering function from one person to eight. Hiring was only the start. The harder, more important work was building a place where strong engineers could do their best work and want to stay.
I mentor directly rather than manage from an org chart. I have been the escalation point and the person who teaches since my early engineering roles. As my team's AI champion and trainer, I ran the demos, proofs of concept, and hands-on sessions that got everyone comfortable with tools that were changing fast.
I protect my team's focus, give credit generously, and take the heat when something breaks. People do their best work when they feel valued, trusted, and appreciated, so that is the environment I work to create.
An open-source memory system that gives AI coding agents persistent, organization-level memory across an engineering team. One Postgres — no Qdrant, no Neo4j, no sync daemons.
Works unchanged across Claude Code, Codex, Copilot, and Kiro over the Model Context Protocol, with namespace isolation over a shared knowledge graph so projects stay cleanly separated while context carries across sessions and clients.
Its compilation pipeline returns ranked, token-budgeted context — not raw search results — with bitemporal fact supersession to keep stale decisions out of working memory.