Healthcare AI Governance Lead
Writes the rules for how a hospital adopts, monitors and retires AI, and makes them stick.
Quick facts
- Which side
- Hospital or health system
- Remote?
- Often hybrid. Policy work travels; the committee meetings and the awkward conversations do not.
- How people get in
- Compliance, clinical informatics, quality and safety, or risk. Increasingly a lateral move from privacy work.
- Pressure from AI
- Growing fast. This role barely existed five years ago and now appears on organization charts.
What the Job Actually Is
A few years ago this was a committee nobody wanted to sit on. Now it is a named job, because boards started asking who signed off.
The work is building the process: how a tool gets proposed, what evidence it needs, who approves it, what gets monitored after it is live, and what triggers switching it off. Then keeping an inventory, because most hospitals genuinely do not know how many models are running inside their systems.
The hard part is not writing the policy. It is that the policy has to be light enough that clinicians follow it and firm enough that it catches a bad purchase.
What You Need to Be Good At
- Turning a framework into a process people actually use
- Keeping a live inventory of deployed models
- Post-deployment monitoring and the authority to pause something
- Knowing which state and federal rules apply and when they changed
Pay
No range is published here. The official United States wage source is the Bureau of Labor Statistics wage survey, which this site cannot query, and every other figure floating around for these roles is scraped or self-reported on a tiny sample. A made-up number would be worse than none.
This is a description of a kind of work, not a job posting, and no openings are listed. Descriptions are editorial and reflect how these teams are commonly staffed rather than any single employer's definition.