About the role
Be the privacy partner to health engineering, product, and clinical stakeholders, guiding privacy decisions across the end-to-end product experience, including feature design, user flows, defaults, and sensitive data use. Set and prioritize privacy controls for health AI scenarios, translate them into clear engineering
requirements, and drive implementation and adoption across the lifecycle. Lead privacy design reviews for health AI features, including data handling, model behavior, and user-facing transparency and choice experiences. Own data governance expectations across the health product lifecycle, including collection, use, sharing, retention, and deletion. Monitor emerging health and data policy developments, assess product impact, and drive prioritized control or experience changes with product and engineering partners. Drive privacy program improvements through repeatable patterns, tooling recommendations, governance and effectiveness metrics, and engineering enablement. Bachelor's Degree AND 8+ years experience in product/service/program management or software development OR equivalent experience 6+ years experience disrupting a market for a product, feature, or experience (e.g., competitive disruption, taking the place of an established competing product) 4+ years of practical experience creating and maintaining compliance programs and conducting privacy reviews. Bachelor's degree in Computer Science or a closely related discipline Experience translating policy and privacy
requirements into shipped product controls in partnership with engineering. Experience leading privacy/compliance engineering programs for AI/ML products or other data-intensive platforms at scale. Hands-on familiarity with regulations related to health verticals, such as HIPAA, GDPR, and similar. Practical experience in health privacy, health policy, and/or health data governance. Working knowledge of health regulations and industry frameworks, including data sensitivity, governance expectations, and common privacy risk patterns. Hands-on experience with privacy engineering practices such as data flow mapping, data classification, consent infrastructure, threat modeling, DSR tooling, retention enforcement, and telemetry governance. Proven ability to lead ambiguous cross-functional work and influence senior leaders without authority, while communicating clearly to engineering and executive audiences. IAPP Certified Information Privacy Professional (CIPP) or Certified Information Privacy Manager (CIPM). Demonstrated team and project management excellence on medium-to-large scale projects, including managing scope, schedule, and budget.
