Practical, hands-on AI experience
I’m a senior software engineer with 28 years of experience building enterprise applications, web and mobile products, integrations, and cloud-hosted systems. My practical AI experience includes prototyping LLM-powered tools, building personal AI projects, and using AI coding tools throughout development.
I've spent my career working where business workflows, architecture decisions, and production delivery meet. These examples show how I contribute when the work has to move from an idea into software people can use and support.
I built ERP software with Ruby on Rails, Meteor, and Backbone, including a Rails API and an offline user interface, while remaining hands-on with delivery.
I delivered an EMA onboarding flow with NestJS, Next.js, Prisma, React Query, and AWS-hosted services, then owned the production migration from the legacy path, documentation, runbooks, and operational handoff.
I delivered the AMC Walking Dead experience through a custom blockchain and JavaScript SDK integration in the Verizon mobile application, including the documented SDK handoff for downstream teams.
As a self-employed Web/Mobile Solutions Architect, I delivered varied client projects spanning custom websites, SaaS applications, and mobile solutions. I worked directly with clients to define workflows, choose practical architecture, build software, and support delivery.
Hiring for a senior software engineering role? Let's talk.
At TxMQ, I led OpenAI research and prototyped LLM-assisted tools as a distinct research track alongside production feature delivery in AngularJS and Ionic.
I built OpenClaw VPS, a personal project for managing hosted AI assistants that is now archived and no longer online. I also use Claude Code, Cursor, and MCP servers throughout development to explore ideas, improve feedback loops, and ship software.
I built FieldBrief as a personal experiment with Azure, Azure Foundry, and Databricks: a workspace for exploring public Texas well records and synthetic production data with an AI assistant that cites its sources.
An oil-well investigation demo built to experiment with Azure, Azure Foundry, and Databricks. Explore well records, compare readings, and ask an AI assistant to explain the evidence. Uses public Texas well records and synthetic production data.
An open-source architecture and production-readiness review platform designed around cited evidence, reproducible scoring, planned AI safety controls, and human approval. Follow the decisions and implementation as the system is built.
OpenClaw VPS was a managed hosting and control-plane product for private, always-on AI assistants. A user could provision and manage a hosted bot, connect an AI provider, chat through the web or a supported messaging channel, and monitor the service without administering the underlying server. The service is not currently online.
First-person grid-based dungeon crawler in the spirit of Eye of the Beholder. D&D on the surface, cosmic horror underneath.
I'm looking for senior software engineering work where I can understand how the business operates, make the important tradeoffs clear, and stay close to implementation through production and handoff.
I bring 28 years of experience across enterprise web, mobile, cloud, integration, and practical AI work. At Key Energy Services, I built ERP software with Ruby on Rails, Meteor, and Backbone, including a Rails API and an offline user interface. More recently, my work at Servant, Nutrien, TxMQ, and Verizon has covered production migrations, offline-first field workflows, OpenAI research, and reusable SDK integration.
I value architecture that helps teams make better decisions and deliver dependable software—not an approval process that slows them down. Read my résumé and cover letter or Message me.
Latest writing
The tools keep changing. My architectural responsibility stays the same: understand the real problem, make tradeoffs visible, and stay accountable through delivery and operation.
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5 min read
I’m building ArchGauge to review architecture evidence and Acme FieldOps to test those reviews against known strengths, defects, fixes, and gaps in evidence.
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6 min read
I am using AI-103 study to connect Azure AI features with the harder work of designing, evaluating, securing, and operating an AI application.
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5 min read
Architects rarely receive complete information. A sound decision makes risk visible, gathers useful evidence, and preserves a safe path to correction.
Read articleI'm pursuing a full-time senior software engineering role. I also offer practical, hands-on architecture support for teams that need focused help.
A focused working session for teams facing a hard architecture or delivery decision. We turn business goals, constraints, and risks into a practical technical direction.
$750
Written decision summary · tradeoffs · prioritized next steps
An evidence-based review of system boundaries, delivery risk, security, operability, and recovery. Findings distinguish facts from assumptions and point to concrete next steps.
Starting at $5,000
Cited findings · risk priorities · remediation roadmap · executive readout
Ongoing architecture leadership for teams that need discovery, system design, delivery guidance, mentoring, and hands-on technical support without adding a full-time role.
Starting at $150/hour · 20-hour monthly minimum
Architecture decisions · delivery guidance · reviews · hands-on support
Considering consulting support? View the consulting profile (PDF)
Tell me what your team is building, where the work is stuck, or what you need from your next senior software engineer.
ArchGauge is being built in public as a complete case study. See the current scope, constraints, decisions, and honest limitations.
View architecture work