Senior Product Manager – Applied Analytics, Data Engineering & AI/GenAI Platforms
- Compensation
- Not disclosed
- Location
- Cupertino
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 10+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Bachelor’s degree in Computer Science, Electrical Engineering, Mathematics, or a related technical field (Master’s degree preferred).
- 10+ years of product management experience building enterprise or platform products.
- Strong experience working with analytics, data engineering systems, data platforms or large-scale distributed infrastructure.
- Demonstrated ability to take products from concept to launch, including vision setting, roadmap ownership, and execution.
- Working knowledge of modern data and AI stacks, including cloud-based data platforms and analytics systems.
Nice to have
- Deep understanding of data engineering concepts such as ingestion pipelines, transformations, batch and streaming systems, metadata, lineage, and governance.
- Experience building or productizing AI/ML or GenAI-powered features
- Familiarity with public cloud platforms (AWS, GCP, or similar) and enterprise-scale deployments.
- Strong systems thinking and the ability to reason about tradeoffs across performance, cost, reliability, and usability.
- Proven ability to influence without authority and build alignment across diverse stakeholder groups.
- Comfort operating in ambiguous problem spaces and shaping direction where requirements are not fully defined.
Full description
Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. We are building the next generation of applied data and AI platforms that power Apple’s most critical services, ranging from Music, TV+, Sports, and Search to emerging AI and GenAI-driven experiences.
We are seeking a Senior Product Manager to lead application-layer data and AI capabilities built on top of Apple’s Data Platform. This role focuses on transforming foundational data infrastructure into developer-facing products, intelligent services, and GenAI-enabled workflows that teams can use to build faster, safer, and more scalable applications.
This is a highly technical, cross-functional role working at the intersection of analytics, data engineering, AI/GenAI systems, and product abstraction.
As a Senior Product Manager for Applied Analytics, Data Engineering & AI/GenAI, you will own product capabilities that sit above Apple’s core data platform and turn into platform capability.
You will partner closely with data platform engineering, AI/ML infrastructure, privacy, security, and application teams to design and deliver:
- Application-layer data services and APIs
- Platform intelligence that helps developers troubleshoot and optimize data pipelines.
- AI and GenAI-powered experiences for data creation, transformation, governance, and analysis
- Tooling that enables developers, analysts, and product teams to safely build data-driven and AI-native applications at scale
You will be responsible for defining product vision, shaping multi-quarter roadmaps, and driving execution from concept through launch, while balancing platform constraints, customer needs, and long-term architectural integrity.
Minimum Qualifications
- Bachelor’s degree in Computer Science, Electrical Engineering, Mathematics, or a related technical field (Master’s degree preferred).
- 10+ years of product management experience building enterprise or platform products.
- Strong experience working with analytics, data engineering systems, data platforms or large-scale distributed infrastructure.
- Demonstrated ability to take products from concept to launch, including vision setting, roadmap ownership, and execution.
- Working knowledge of modern data and AI stacks, including cloud-based data platforms and analytics systems.
Preferred Qualifications
- Deep understanding of data engineering concepts such as ingestion pipelines, transformations, batch and streaming systems, metadata, lineage, and governance.