Principal AI & Data Governance Architect

At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. We are building the machine learning lifecycle platform that powers generative AI features across Apple Services — from Music and TV+ to iCloud, App Store, and Sports. As these systems grow in scale and complexity, building them responsibly is as important as building them well.

We are looking for a AI & Data Governance Architect who can define and drive the governance and compliance architecture for our AI and ML platform — holistically, not piecemeal. This is not a role about enforcing rules from the sidelines. It is about getting deep into how data flows, how models are built, how systems interconnect, and designing the platform capabilities that ensure Apple meets its legal, regulatory, and ethical obligations at every layer. You will be the person who understands both the compliance landscape and the engineering reality — and who builds the bridge between them.

Minimum Qualifications

Deep experience in data governance, ML governance, or compliance architecture within complex, large-scale technical environments.
Deep understanding of ML workflows, data engineering, and ML infrastructure — drive and provide feedback in design and architectural discussions.
Proven track record of working cross-functionally with legal, privacy, compliance, and engineering teams to define and implement governance solutions.
Demonstrated ability to refine legal and regulatory requirements into technical architecture and engineering deliverables.
Fluent in both legal and engineering languages — able to take prescriptive or loosely defined compliance obligations and translate them into precise technical requirements without losing the spirit of the original intent.
Experience engaging upstream with legal and policy stakeholders to shape policy guidance, ensuring that it is technically coherent.
Exceptional ability to operate in ambiguity — connecting requirements that don't come pre-connected, and driving clarity across organizations with different vocabularies and priorities.

Preferred Qualifications

Familiarity with AI/ML regulatory frameworks and emerging legislation (e.g., EU AI Act, GDPR, CCPA, data residency requirements).
Experience designing or implementing data classification systems, data catalogs, or model registries in a production ML environment.
Experience building governance frameworks for internal developer platforms or MLOps tooling.
Comfortable presenting complex compliance and architectural topics to senior and executive engineering and legal audiences.
Bachelor’s degree in Computer Science or similar degree. Master's degree preferred.