Drimva

Apple

Director of Privacy Engineering, Services

$311K–$497K

Cupertino, California · Director · Full-time · Posted Jul 22, 2026

Experience
15+ years of software development, including 5+ years leading engineering organizations with multiple layers of management and 3+ years in privacy leadership.
Education
Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.

About the job

Leads Apple Services Engineering’s privacy organization, building privacy-preserving systems and practices and advising leaders and teams on privacy strategy, including challenges from AI features.

What you'll do

  • Set technical direction, structure, and culture for the privacy engineering organization; recruit and develop talent.
  • Direct privacy-enabling services, tools, and platforms, and scale privacy-by-design guidance and education across Apple Services Engineering.
  • Advise stakeholders and lead privacy approaches for AI features and regulatory compliance, including GDPR.

What they ask for

  • 15+ years of software development experience, including 5+ years leading engineering organizations with multiple management layers and 3+ years in privacy leadership.
  • Experience recruiting and developing leadership talent and building high-performing engineering cultures at scale.
  • Deep expertise designing, building, and operating large-scale privacy systems, tools, and infrastructure; command of privacy-enhancing technologies.
  • Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.

Nice to have

  • Experience addressing AI/ML privacy challenges, including training data governance and model inference privacy.
  • Experience with privacy strategy, privacy regulations such as GDPR and CCPA, or geographically distributed teams.

Pay

$311,100 and $496,900 USD base salary

Tools

differential privacy, federated learning, on-device processing, tokenization, data de-identification, GDPR, CCPA

AI focus

Lead the invention of privacy approaches for AI features, including challenges such as training data governance and model inference privacy.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 5, 2026 (UTC)