About The Position
The AI Adoption & Governance Analyst operationalizes AI standards across the Patient Services engineering organization and proves the SDLC transformation in metrics. This role is the connective tissue of the AI Hub COE: rolling out AI development tooling to Dev, QA, and BA teams; owning the governance artifacts that keep AI use safe and compliant; and reporting the adoption and ROI story to leadership. It is the right role for someone who blends analytical rigor with strong communication and change-management instincts — someone who can drive real adoption of new ways of working, not just publish a policy. Mission: Operationalize AI standards across BA, QA, and Dev — and prove the SDLC transformation in measurable adoption and ROI.
Requirements
- 3+ years in a technical analyst, program enablement, developer-experience, or similar role.
- Strong data analysis and dashboarding skills.
- Excellent technical writing and documentation ability.
- Demonstrated change-management and training-delivery experience.
- Working fluency with AI tooling ecosystems (Claude, Gemini, AI coding assistants) — able to teach and support their use.
- Understanding of HIPAA, SOC 2, or comparable privacy/compliance fundamentals.
- Strong cross-team coordination and stakeholder-communication skills.
Nice To Haves
- Background in healthcare or life-sciences technology.
- Experience supporting or governing an AI or developer-tooling rollout at scale.
- Familiarity with JIRA, Confluence, and BI tools (Looker, Tableau, or BigQuery).
Responsibilities
- Roll out AI development tooling — Claude Code, GitHub Copilot, Cursor — as engineering standards across the Patient Services teams.
- Train and onboard Dev, QA, and BA staff into AI-augmented ways of working; run office hours, certification, and internal forums.
- Own the AI best-practice wiki, training materials, and the agent registry.
- Own and maintain the prompt library governance process, including quality gates before templates are promoted.
- Conduct HIPAA/PHI compliance reviews of AI tool usage; coordinate with InfoSec on data-flow approval and risk sign-off.
- Maintain the approved-tools list and the AI risk register.
- Support model-selection and BAA-verification processes led by the AI Engineering & Enablement Lead.
- Define and track AI adoption KPIs: AI velocity, code-generation percentage, defect-rate delta, time-to-merge, and story points per sprint.
- Author monthly team adoption reports and quarterly executive ROI dashboards for the CTO and CFO.
- Surface adoption gaps and recommend interventions to the AI Engineering & Enablement Lead.
Benefits
- Certified as a Great Place to Work across the globe
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
