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

Apple•Sunnyvale, CA

About The Position

Apple’s AI and Data Platform (AiDP) team is building generative AI capabilities—including knowledge discovery, conversational capabilities, workflow automation, and developer productivity—to increase productivity and efficiency across Apple’s business units. As the challenges shift toward making AI trustworthy, governable, and reliable at enterprise scale, the team is seeking a Product Manager to address consequential product challenges in this evolving space. The Product Manager will define, build, launch, and iterate on products and capabilities that shape how AI is deployed and operated across Apple. The role sits at the intersection of AI/ML, enterprise infrastructure, security, and developer experience, and involves close partnership with engineering, security, data science, and business teams. The successful candidate will bring technical depth, think in systems and architectures, prototype to learn quickly, navigate organizational boundaries, influence stakeholders, and manage a portfolio of products in a rapidly evolving category.

Requirements

At least 2 years of experience working on platform, infrastructure, developer tools, or enterprise systems products.
Experience shipping AI/ML-powered products in production environments, rather than only prototypes or demos.
Strong technical background and ability to engage meaningfully with senior engineers on system architecture, API design, and security trade-offs.
Hands-on proficiency with AI coding tools such as Claude Code, Cursor, Replit, or equivalent for rapid prototyping and idea validation.
Experience working cross-functionally with engineering, security, design, and business stakeholders.
Bachelor’s degree in Computer Science, Engineering, Data Science, or a similar field, or equivalent practical experience.
At least 3 years of product management experience.
Excellent written and verbal communication skills, including the ability to influence without direct authority.
Strong analytical skills and a data-driven approach to prioritization and decision-making.

Nice To Haves

Advanced technical degree, such as a Master’s in Computer Science, Engineering, or 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 are core product capabilities.
Background in cloud-native architectures, distributed systems, or container orchestration.
Working proficiency in Python and SQL.
Experience driving platform or product adoption across large organizations with multiple independent teams.
Experience evaluating build-versus-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.

Responsibilities

Define and execute product strategy, roadmap, and delivery for GenAI capabilities serving Apple’s enterprise teams.
Make product decisions involving technical architecture, including system design, protocol choices, security models, and infrastructure trade-offs, in partnership with senior engineers.
Partner with teams across Apple to understand AI needs, articulate user journeys and use cases, identify pain points, and translate findings into product requirements.
Build prototypes and proof-of-concepts using AI coding tools to validate ideas hands-on.
Drive adoption of products and capabilities across multiple internal teams, often through influence rather than authority.
Track the competitive landscape across GenAI products, agentic systems, orchestration frameworks, and emerging protocols to inform product direction.
Research industry approaches and conduct technical teardowns of competitor offerings.
Define and measure success using metrics frameworks, including designing KPIs for new products.
Understand technical problems and dependencies, and partner with cross-functional teams to ensure effective launches and a high-quality product experience.
Translate complex technical concepts into clear product specifications, user stories, and prioritized backlogs.
Discuss industry-specific business and technical concepts with executives, managers, and technologists.
Communicate product vision, strategy, and progress to audiences ranging from engineers to senior executives.