VP of AI

The VP of AI & Automation owns a single mandate: systematically examine how XRHealth operates, and redesign those operations with AI and automation so the company runs faster, leaner, and with better data at every decision point.

This is an internal transformation role, not a product role. You will work across clinical operations, revenue cycle, finance, HR, IT, legal, marketing, and sales — mapping processes, quantifying waste, and shipping working systems. You will partner closely with product and engineering where internal work touches the patient-facing platform, but your accountability is the operating company.

You will be given broad access and expected to act with judgment. In a regulated healthcare environment, that means every solution you build must be defensible on privacy, security, and clinical-safety grounds from day one.

• Build and maintain an end-to-end map of XRHealth’s core processes, including cycle times, handoffs, error rates, and cost per transaction.
• Maintain a prioritized, quantified backlog of AI and automation opportunities, scored on effort, risk, and measurable financial or time impact.
• Bring a defensible ROI case to every initiative before it is funded, and report actuals against it afterward.

• Deliver working solutions — not decks. This includes LLM-based workflows, agentic tooling, document and claims processing, intelligent routing, reporting automation, and integrations across our systems.
• Own the full lifecycle: design, build or buy, pilot, measure, scale, and retire.
• Drive adoption. A deployed tool that no one uses is a failed project; you are responsible for the training, change management, and follow-through that make new ways of working stick.

• Establish and own XRHealth’s AI governance framework: acceptable-use policy, model and vendor review, PHI handling standards, BAA requirements, human-in-the-loop requirements for clinical-adjacent workflows, audit logging, and incident response.
• Ensure every AI system is consistent with HIPAA, applicable state privacy law, our SOC 2 / HITRUST posture, and international requirements including GDPR where our non-US entities are in scope.
• Be the internal authority on where AI should not be used.

• Partner with our data team to make internal data usable for AI: schema quality, lineage, access controls, and the gold-layer models that AI workflows depend on.
• Own the internal AI tooling stack and vendor relationships, including cost management and consolidation.

• Raise the AI literacy of the whole company: role-specific training, internal playbooks, prompt and pattern libraries, and a clear path for any employee to propose or prototype an improvement.
• Build a small, high-leverage team over time. Start hands-on.

• Complete a process and systems audit across all major functions, with baseline metrics.
• Deliver a prioritized 12-month roadmap with quantified impact and resourcing needs, approved by leadership.
• Ship two to three high-confidence quick wins that demonstrate value and build internal credibility.
• Publish v1 of the AI governance and acceptable-use policy.

• Measurable reduction in cycle time and manual effort in at least four core processes, with documented before-and-after metrics.
• Documented annualized savings or capacity gain that materially exceeds the fully loaded cost of the function.
• AI governance operating in practice, with a clean review trail for every production workflow touching PHI.
• Demonstrated organization-wide adoption, not isolated pilots.

• 8+ years in operations, technology, data, or transformation roles,…