Product Manager — Generative Ai, AI & Data Platforms (aidp)

Apple Apple · Big Tech · Sunnyvale, CA · Corporate Functions

Product Manager for Generative AI within Apple's Ai & Data Platforms team, focusing on building and scaling GenAI capabilities for enterprise use cases like knowledge discovery, conversational AI, and workflow automation. The role involves defining product strategy, working closely with engineering and data science, and ensuring AI is trustworthy, governable, and reliable at scale. Requires a technical background, ability to prototype, and experience shipping AI/ML products.

What you'd actually do

  1. Define and execute product strategy, roadmap, and delivery for GenAI capabilities that serve Apple's enterprise teams
  2. Make product decisions that are deeply intertwined with technical architecture — you will engage on system design, protocol choices, security models, and infrastructure trade-offs alongside senior engineers
  3. Partner with teams across Apple to understand their AI needs, articulate user journeys and use cases, identify pain points, and translate those into product requirements
  4. Build prototypes and proof-of-concepts using AI coding tools such as Claude Code, Cursor, or similar — we expect PMs to "vibe code", validate ideas hands-on, and stay close to the technology rather than only writing specs
  5. Drive adoption of products and capabilities across multiple internal teams, often through influence rather than authority

Skills

Required

  • 2+ years working on platform, infrastructure, developer tools, or enterprise systems products
  • Experience shipping AI/ML-powered products in production environments, not just prototypes or demos
  • Strong technical background with the ability to engage meaningfully with senior engineers on system architecture, API design, and security trade-offs
  • Hands-on proficiency with AI coding tools (Claude Code, Cursor, Replit, or equivalent) for rapid prototyping and idea validation
  • Experience working cross-functionally with engineering, security, design, and business stakeholders
  • Strong analytical skills with a data-driven approach to prioritization and decision-making
  • Excellent written and verbal communication skills with the ability to influence without direct authority
  • Bachelor’s Science Computer Science, Engineering, Data Science, or similar, or equivalent practical experience

Nice to have

  • 5+ years of product management experience
  • Advanced Degree Technical degree (i.e., Master in Computer Science, Engineering, Data Science) or equivalent practical experience
  • Experience with agentic AI systems, agent frameworks, orchestration engines, or multi-agent architectures
  • Familiarity with emerging AI infrastructure protocols and standards for tool integration, agent interoperability, and workload identity
  • Experience building products where governance, compliance, audit trails, and access control were core to the product rather than afterthoughts
  • Background in cloud-native architectures, distributed systems, or container orchestration
  • Python and SQL working proficiency
  • Experience driving platform or product adoption across large organizations with multiple independent teams
  • Experience evaluating build-vs-buy decisions and technology partnerships
  • Understanding of enterprise security patterns including delegated authorization, policy enforcement, and runtime isolation
  • Familiarity with the GenAI competitive landscape including offerings from major cloud providers and key startups

What the JD emphasized

  • ship AI/ML-powered products in production environments
  • Hands-on proficiency with AI coding tools
  • Experience with agentic AI systems, agent frameworks, orchestration engines, or multi-agent architectures
  • Familiarity with emerging AI infrastructure protocols and standards for tool integration, agent interoperability, and workload identity
  • Experience building products where governance, compliance, audit trails, and access control were core to the product rather than afterthoughts

Other signals

  • define and execute product strategy, roadmap, and delivery for GenAI capabilities
  • partner closely with engineering, security, data science, and business teams
  • define and measure success through metrics frameworks
  • ship AI/ML-powered products in production environments