Engineering leader · Founder · Mesa, Arizona
Thirty years in software. Today I lead a 26-engineer global organization, run Clarity Technologies — the consultancy I founded in 2014 — and own two junior hockey teams whose software I wrote myself.
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The threadWhat it touches
About
The person behind the graph. Based in Mesa, Arizona, married with five kids and a house full of cats and dogs. Thirty years across engineering, architecture and technology leadership; when the laptop closes, it's usually a rink, a field, or a flight to Maui.
Chapter 01
Since 2014 my career has run on two parallel tracks. On one, I lead engineering organizations — in regulated industries where hand-waving doesn’t survive an audit.
On the other, I build software independently through Clarity Technologies, for clients in financial services, healthcare and IoT.
LEADING
Development, automation, modernization and AI. The unglamorous discipline that makes releases boring.
BUILDING
Architecture strategy and full-cycle delivery — increasingly centred on AI and agentic automation.
THE PATH
Career
A career measured in scope and capability rather than a list of logos. Two tracks running in parallel since 2014: leading engineering organizations, and building software independently through Clarity Technologies.
Career
Founded 2014 and still running. Engineering leadership, architecture strategy and full-cycle delivery for clients across financial services, healthcare and IoT, increasingly centred on AI and agentic automation.
Career
Building teams and the systems of work around them: engineering standards, delivery cadence, architecture review, and the unglamorous discipline that makes releases boring.
Career
Two decades inside lending technology: loan origination, broker systems, point of sale, and the integration surface between them. Regulated, audited, and unforgiving of hand-waving.
Expertise
Designing how large systems fit together: integration frameworks, API strategy, identity, data movement, and the migration paths that get legacy platforms to somewhere maintainable.
Achievement
Milestones with a number attached, and the credentials behind them.
Achievement
Currently leading a 26-member global engineering team spanning development, automation, platform modernization and AI initiatives.
Achievement
Three active certifications from Ellie Mae / ICE Mortgage Technology, maintained and renewed rather than collected once.
Achievement
Bachelor of Applied Science in Technology Management, Northern Arizona University, 2014.
Chapter 02
Twice, in two different organizations, a commercial point-of-sale product stopped fitting the business — and twice I replaced it with a custom build. One went from nothing to a production-ready prototype in ten months.
Analysis still happens first. But when the right tool doesn’t exist, build it.
Retail
Two commercial products replaced with in-house builds — better UX, scale and cost each time.
Mortgage
A .NET platform for one of the largest mortgage brokerages in the U.S. — APIs across LOS, CRM, ERP and third parties.
Loyalty
$50M+ in global rebate and loyalty programs, a channel incentive engine and 100+ rebate sites.
IoT
LoRaWAN sensors with thresholds, escalation, auto-resolution and SMS/email alerting.
A pattern
A recurring decision, surfaced by the graph rather than stated anywhere: when a commercial platform stopped fitting the business, it got replaced with a custom build. Twice, in two different organizations. Analysis still happens first, but when the right tool for the job doesn't already exist, build it. With AI in the mix, that calculus has only shifted further.
Project
Two separate commercial point-of-sale products replaced with custom in-house platforms. One reached a production-ready prototype in ten months with a hybrid onshore/offshore team.
Achievement
A custom point-of-sale platform taken from nothing to a production-ready prototype in ten months, replacing a commercial product, with a hybrid onshore/offshore team.
Project
A .NET loan origination platform serving one of the largest mortgage brokerages in the United States. Engineering strategy, enterprise API architecture, modernization and AI initiatives.
Project
An enterprise promotions and incentive platform supporting more than $50M in global rebate and loyalty programs, including a channel incentive engine and over one hundred consumer-facing rebate sites.
Achievement
Technology leadership for global rebate and loyalty programs exceeding $50M across hundreds of client brands.
Project
Sensor and gateway integration over LoRaWAN with event-driven monitoring: configurable thresholds, escalation, automatic resolution, connectivity and battery health, and SMS/email alerting for operational and compliance use.
Expertise
Long-range low-power sensor networks: gateways, device provisioning, telemetry processing and the alerting layer that makes the data actionable.
Expertise
Deep platform-level knowledge of lending technology: extending, integrating and migrating the systems the industry actually runs on.
Expertise
Connecting systems that were never designed to meet (origination platforms, CRMs, ERPs, document systems and warehouses) reliably and repeatably.
Expertise
The through-line of the whole career. C#, .NET, SQL and the SDK-level work that extends enterprise platforms rather than merely configuring them.
Chapter 03
Seven years in Phoenix youth hockey turned into something most people wouldn’t attempt: I own and operate two junior hockey organizations — the Salt Lake Ghost Riders and the Hudson Havoc.
A team is a business: players, staff, host housing, schedules, budgets. So I wrote the software that runs them.
I’m my own first customer. The requirements come from the rink, not a backlog.
Registration, rosters, trades and waivers, scheduling and in-app document signing. Fifteen business modules on .NET 10 and React 19.
The multi-tenant layer above a single team: subscriptions, usage metering and invoicing — money stored as integer cents, never floats.
Junior players live with host families. This matches athletes to homes — an unglamorous, genuinely hard problem.
A pattern
He owns and operates two junior hockey organizations, and writes the platforms that run them. League Manager, Team Manager and Billet Manager exist because he needed them himself. He is his own first customer, which means the requirements arrive from the rink rather than from a backlog.
Off the clock
Seven years in youth hockey in Phoenix, Arizona. Mentoring and supporting young athletes, and coaching the same things that matter at work: dedication, teamwork, showing up.
Off the clock
Owner / operator. A USPHL Premier junior hockey organization: a business with players, staff, housing, schedules and budgets, not a weekend hobby.
Off the clock
Owner / operator. Competing at both NCDC and Premier levels: two tiers, two rosters, and roughly double the operational surface.
Project
A hockey league management platform: registration, rosters, trades and waivers, scheduling, document signing, compliance, finance and statistics. Built as a modular monolith so fifteen business domains stay genuinely separable. In active development, operating his own organizations.
Project
The multi-tenant layer above a single team: organizations, subscriptions, usage metering and invoicing, with strict tenant isolation enforced at the database. In active development.
Project
Junior hockey players live with host families. This matches athletes to host homes: availability windows, compatibility, placement staging and onboarding. An unglamorous, genuinely hard operational problem. In active development.
Off the clock
Building and scaling ventures: a consulting firm since 2014, a hockey organization, and independent software products.
Chapter 04
The same instinct now points at AI. At Clarity the work is agent architecture, private inference and automation — systems where models do the judgement and deterministic tools do the arithmetic.
And data doesn’t leave the building unless it should.
Built by a father of five
A parent-controlled viewing platform where every video is reviewed before a child can watch it. AI reads the captions and metadata; parents approve or block — and revoking access stops playback already in progress.
In active development
Two nodes running open-weight models locally, routed by job: fast, reasoning, or burst for the genuinely hard problems.
Specialised agents that are packaged, permissioned and delegated to by a broker — not left to spawn each other freely.
Decision support and a companion iOS app for people caring for loved ones with dementia.
THE TOOLBOX UNDERNEATH
.NET & C# · Azure & AWS · SQL Server to Qdrant · APIs & integration · LoRaWAN · Encompass & ICE · RAG & model routing
Career
Leading adoption of AI inside engineering organizations: evaluating models, standing up infrastructure, and finding the workflows where automation actually pays for itself.
Expertise
Designing systems where models do the judgement and deterministic tools do the arithmetic. Agent architecture, retrieval, orchestration and the operational discipline to run it privately.
Project
A private, two-node inference cluster running open-weight models locally. No data leaving the building. Models are tiered by job: a fast model for routine execution, a reasoning model for analysis, and a burst model brought online only for genuinely hard problems.
Project
A multi-agent platform where specialised agents are packaged, permissioned and delegated to. A broker ranks candidate agents by capability, permission coverage and queue depth rather than letting agents spawn each other freely.
Project
An automation system and companion iOS app supporting caregivers of dementia patients, applying AI-driven decision support and behavioural recommendations at the point of care.
Project
A parent-controlled viewing platform: every video is reviewed before a child can watch it. AI-assisted review reads metadata and captions, parents approve or block, and revoking access interrupts playback already in progress. Built by a father of five. In active development.
Project
Systems that shipped and stayed shipped. Client engagements are described without naming the client; independent work is named directly.
Expertise
Capability shown through what it built, not through a percentage bar. Every branch here connects to the work that evidences it.
Expertise
Azure and AWS, containers, and the pipeline discipline that turns deployment from an event into a routine.
Expertise
Relational, document and vector stores, plus the warehousing and reporting layers that make them useful to a business.
Chapter 05
Home is Mesa, Arizona — married, five kids, and a house full of cats and dogs.
Football is the second season to hockey. And every chance I get, it’s a flight to Maui, the one place I keep going back to.
Education: B.A.S. in Technology Management, Northern Arizona University, 2014.
Off the clock
The parts that aren't on the résumé but explain a fair amount of it.
Off the clock
Travels every chance he gets. Maui is the one he keeps going back to (the place that wins even against everywhere else on the list).
Off the clock
The other sport. Watched more than played these days, and a reliable second season to hockey.
That’s the story. Now wander it yourself.
The map
Every project, skill and team on this site is a point on the map. Follow a thread, or click any point to see what it touches.
Hover a point to see its name. Click it to see everything it connects to.
Consulting, technology leadership, AI and automation. There’s no résumé to download on purpose — a conversation is the best path to detail.
The easiest way to reach me directly is email.