Join Apple’s Data Platform as a Staff GenAI Engineer, where you'll be at the forefront of delivering transformative AI experiences across Apple products, including Apple Music, TV, Sports and many more. You will play a pivotal role in defining and driving the roadmap for Apple Data Platform's GenAI Platform component, which powers the development, evaluation, and deployment of AI agents and applications. This includes building foundational capabilities such as agent orchestration, model configuration, prompt tooling, RAG integration, and inference optimization enabling teams across Apple to rapidly create scalable, context-aware GenAI solutions.You will collaborate closely with cross-functional teams of innovative software engineers, product managers, and engineering leaders to continuously evolve the platform for performance, flexibility, and ease of use.RESPONSIBILITIES INCLUDE:* Define and drive the technical vision, roadmap, and strategy for Apple Data Platform’s GenAI components, enabling scalable development and deployment of AI applications powered by LLMs and agentic workflows* Guide the design and development of platform capabilities such as agent orchestration, RAG integration, LLM model configuration, prompt tooling, and fine-tuning pipelines* Drive efforts around LLM inference optimization, including caching, prompt tuning, and latency improvements, ensuring efficient and cost-effective model usage across applications* Collaborate with engineering, product, and operations teams across Apple to ensure effective adoption of GenAI capabilities in high-impact workflows* Partner with stakeholders to build reusable AI agents that enhance productivity, automate reasoning tasks, and integrate securely with internal systems and tools* Mentor new hires and fellow engineers, fostering growth in technical depth and platform mindset* Establish best practices and processes that ensure engineering excellence, operational sustainability, and a seamless developer experience* Promote a healthy, inclusive, and innovation-driven team culture with a focus on experimentation, learning, and long-term platform impact