AI Program & Governance Lead

Thyme Care Thyme Care · Healthcare · Remote · Legal & Compliance

This role leads the AI program and its governance at Thyme Care, focusing on ensuring AI is used safely and effectively while expanding its scope. The lead will manage AI risk through tooling, infrastructure, guidance, training, and controls, working closely with various teams to enable AI adoption and ship value in production products and workflows. The role requires technical depth and program management experience in regulated environments, with a focus on operationalizing AI governance, risk reviews, and enablement without hindering development.

What you'd actually do

  1. Own AI governance intake: ensure pilots, purchases, and launches go through proper security and risk reviews before they happen
  2. Facilitate governance committee reviews and drive decisions to resolution
  3. Build and maintain the operational infrastructure of our AI program: documentation, audit trails, escalation pathways
  4. Operationalize evals, labeling and monitoring in ways that serve PMs, engineers, clinicians and other cross-functional stakeholders
  5. Own training and enablement: help non-technical teams understand AI capabilities, governance and potential opportunities for value

Skills

Required

  • AI governance
  • AI risk management
  • Program management
  • Technical foundation (software engineering or security engineering)
  • Cross-functional facilitation
  • Operational rigor (documentation, audit trails, process improvement)

Nice to have

  • HIPAA or healthcare security/privacy experience
  • Experience implementing governance for AI or ML/LLM systems
  • Vendor risk and procurement coordination
  • Enablement/training programs for non-technical audiences

What the JD emphasized

  • AI Program & Governance Lead
  • manage AI risk
  • technical depth
  • software engineering or security engineering background
  • practical controls and enablement
  • AI Governance Committee
  • AI governance intake
  • security and risk reviews
  • operational infrastructure
  • audit trails
  • escalation pathways
  • Operationalize evals, labeling and monitoring
  • training and enablement
  • AI controls into practical, operationalized team workflows
  • Governance decisions happen quickly and with clear rationale
  • clean audit trails
  • effective controls
  • implementing governance for AI or ML/LLM systems

Other signals

  • AI Governance
  • AI Risk Management
  • AI Program Management
  • AI Enablement
  • AI Controls