The Engineering Manager, AI Data Platforms & Quality will lead the Manufacturing Systems and Infrastructure team at Apple, focusing on building next-generation AI data products and platforms. This role requires a strong engineering leader with expertise in data platforms and AI data engineering. The manager will drive the technical strategy for transforming enterprise data into trusted, AI-ready assets. Collaboration with AI/ML, product, and business teams is essential to accelerate the development of high-quality data assets.

• Experience leading solution and data engineering teams building large-scale, production-grade systems.
• Strong background in data engineering, distributed systems, and cloud-based data platforms.
• Proven experience designing and building scalable data products, data pipelines, APIs, and platform services.
• Experience with AI data lifecycle management, including dataset curation, validation, quality evaluation, metadata management, lineage, and governance.
• Strong expertise in AI Data Platforms & Engineering, including Python, SQL, Spark, Airflow, Kafka, data pipelines, distributed systems, and modern data lake/lakehouse architectures.
• Experience building AI Data Curation & Quality capabilities, including dataset engineering, validation frameworks, data profiling, observability, and data quality metrics.
• Understanding of GenAI enablement technologies, including LLM applications, RAG architectures, embeddings, and AI agent workflows.
• Experience with cloud and infrastructure technologies, including AWS/GCP/Azure, Kubernetes, Docker, CI/CD, and scalable production systems.
• Demonstrated ability to define technical strategy, drive architecture decisions, lead complex execution, and collaborate effectively across cross-functional teams.
• Experience building AI data platforms or infrastructure supporting LLM applications and AI products.
• Experience with multimodal data including text, image, video, sensor, or operational datasets.
• Experience building data quality frameworks, AI evaluation pipelines, or dataset management platforms.
• Experience translating emerging AI technologies into scalable enterprise solutions.
• Strong communication skills with the ability to influence technical direction across organizations.

• Lead the team's expanded charter to build next-generation AI data products and platforms.
• Define and drive the technical strategy for transforming enterprise, operational, and multimodal data into trusted, AI-ready assets.
• Collaborate with AI/ML, product, and business teams to accelerate the development of high-quality data assets.
• Build and scale foundational capabilities for AI data lifecycle management, including data ingestion, curation, validation, quality, governance, metadata management, and observability.
• Deliver scalable AI-powered data products and platforms.

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.