Engineering Manager, AI Data Platforms & Quality

Imagine what you could do here. At Apple we believe new insights have a way of becoming excellent products services and customer experiences very quickly. Bring passion and dedication to your job and theres no telling what you could people here at Apple dont just build products they build the kind of wonder thats revolutionized entire industries. Its the diversity of those people and their ideas that inspires the innovation that runs through everything we do from amazing technology to industry-leading environmental efforts. Join Apple and help us leave the world better than we found Systems and Infrastructure (MSI) team is an engineering organization under the Product Operations org. MSI is responsible for the design development and maintenance of systems tools services and applications required to efficiently run manufacturing operations at scale across global factory ideal candidate is a strong engineering leader with deep expertise in data platforms AI data engineering and modern AI application architectures. This leader will build and scale the foundational capabilities for AI data lifecycle managementincluding data ingestion curation validation quality governance metadata management and observabilitywhile delivering scalable AI-powered data products and platforms. Success in this role requires close partnership with AI/ML product and business teams to accelerate the development of high-quality data assets that fuel enterprise AI innovation.n

As the Engineering Manager AI Data Platforms u0026 Quality within the MSI organization you will lead the teams expanded charter to build next-generation AI data products data platforms and data quality capabilities that enable GenAI agentic AI and embodied AI initiatives. You will define and drive the technical strategy for transforming enterprise operational and multimodal data into trusted AI-ready assets that power intelligent applications AI agents analytics and automated workflows.n

Lead and grow a high-performing engineering team focused on AI data platforms data products data quality and GenAI technical vision architecture and roadmap for scalable AI data platforms and AI-ready data reusable platform capabilities for data ingestion processing curation validation data quality management metadata lineage and development of AI-ready datasets supporting GenAI agentic workflows and embodied AI AI applications through RAG pipelines embeddings vector search knowledge systems and AI data engineering best practices for scalability reliability observability security and operational with AI/ML engineers product teams and business stakeholders to identify opportunities and deliver impactful AI engineers develop technical talent and foster a culture of innovation and engineering excellence.

Experience leading solution and data engineering teams building large-scale production-grade background in data engineering distributed systems and cloud-based data experience designing and building scalable data products data pipelines APIs and platform with AI data lifecycle management including dataset curation validation quality evaluation metadata management lineage and expertise in AI Data Platforms u0026 Engineering including Python SQL Spark Airflow Kafka data pipelines distributed systems and modern data lake/lakehouse building AI Data Curation u0026 Quality capabilities including dataset engineering validation frameworks data profiling observability and data quality of GenAI enablement technologies including LLM applications RAG architectures embeddings and AI agent with cloud and infrastructure technologies including AWS/GCP/Azure Kubernetes Docker CI/CD and scalable production 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 with multimodal data including text image video sensor or operational building data quality frameworks AI evaluation pipelines or dataset management translating emerging AI technologies into scalable enterprise communication skills with the ability to influence technical direction across organizations.