University of Utah - Director of AI Integration
The U needs senior AI leadership. The salary band won't attract it. Fractional solves that.
People who have actually led AI integration at scale - built the programs, managed the vendors, transformed organizations, and shipped systems that worked - command $300K-$500K+ in total comp. At $100K-$120K, the U will get applicants who are adjacent to that work, not accountable for it. A fractional engagement is a different structure: senior experience scoped to what the University actually needs, at a cost that fits the budget.
I graduated from the David Eccles School of Business. I spent nearly a decade at Microsoft - as a software engineering manager, principal engineer, and ultimately Sr. Director of Partner Ecosystem for AI/ML - building the programs that connected universities and employers across the country. I ran a $51M P&L transformation into AI/ML managed services. I'm local, I know the institution, and I'm currently building and operating a production AI platform in Salt Lake City.
What the position requires. What I bring to it.
The U's job posting, mapped against actual experience.
“Architect and lead a statewide AI integration strategy”
At Microsoft, I designed and executed AI strategy across hundreds of partners, universities, and employers spanning multiple states and countries. I know what a statewide program requires structurally - and where these initiatives typically break down two years in.
“Collaborate with industry and higher education partners to develop AI-centric curricula and certification programs”
I built the AI partner enablement programs that connected the Microsoft ecosystem to universities and employers at scale - AI Accelerate, the Data Science Partner Program, AI Country Plans. The U already has strong industry relationships through Silicon Slopes. I know how to activate them for something like this.
“Establish performance indicators to measure the impact of AI-related initiatives”
I've run $1.5M in AI initiative funding and tracked it to $25M+ in measurable outcomes. I can build the measurement framework this program needs - one that will hold up when the legislature or the board asks how it's going.
“Develop AI upskilling programs for faculty, staff, and students”
Training design and change management for AI adoption is something I've done at organizations ranging from 200-person teams to partner networks across multiple countries. Faculty adoption in particular requires a different approach than corporate upskilling. I've thought carefully about this.
“Governance, policy, and responsible AI frameworks”
Academic AI governance has to work in a shared governance environment - faculty senate, IRB considerations, student data, research integrity. I can build a framework that doesn't just satisfy a compliance checklist, but actually holds up in practice.
“Implementation oversight and vendor evaluation”
The AI vendor landscape is full of promises. I can read a proposal and tell you whether the architecture will actually do what they say. No vendor relationships to protect. No kickbacks. Just an honest assessment.
Background
The experience that makes this relevant.
MBA, David Eccles School of Business
I understand the University's context - the academic priorities, the faculty governance structure, the relationship between the U and the state, and the Silicon Slopes industry ecosystem the U is already embedded in. This isn't a national search candidate who will spend their first year learning the landscape.
Built the Microsoft AI/ML partner programs that connected employers and universities
AI Accelerate, the Data Science Partner Program, AI Country Plans. Curriculum design, employer certification pathways, and adoption programs built at scale across the US and multiple countries. The institutional partnership model the U is describing is work I've done - just at the Microsoft partner ecosystem level.
Led AI transformation at P&L accountability level
As GM at Crayon US, transformed a $43M to $51M business from a traditional reseller into a full AI/ML managed services provider. Not advisory work - building practices, hiring, service delivery, and go-to-market. The credibility to lead an AI integration strategy comes from having been responsible for one.
Shipping production AI in Salt Lake City today
SnappyClaw is a live, multi-tenant AI agent platform with enterprise customers. When I advise on AI tools, implementation risk, or what a curriculum should prepare students to work with, it is grounded in what is actually working in production systems in 2026 - not white papers or vendor roadmaps.
Credentials
If it's worth a conversation
I'm local, I know the institution, and I have done exactly this kind of work. If the Dean or the hiring team wants to talk through what a fractional engagement could look like for what the U is trying to build, I'm easy to reach.