Principal AI Architect, App Store Data

Job description

Apple's App Store is the world's largest and most innovative app marketplace, home to over 1.5 million apps and serving more than half a billion customers every week across all Apple devices. Since the App Store launched in 2008, it has changed how we all live; it has enabled countless new companies, spawned new industries, and built millions of jobs. But we believe we are just getting started. Our team enables data-driven innovation for internal and external partners, while maintaining data quality, privacy, and engineering excellence as first-class citizens. We're looking for a highly skilled hands-on Principal AI Architect with strong software development skills and a passion for applying LLMs and Agentic workflows to real-world business problems. Description In this role, you will design and ship AI systems that make App Store data useful, safe, and actionable - from agentic workflows that automate analytical tasks, to LLM-powered data products that surface insights. The ideal candidate is someone who moves fluidly from prototype to production, writes the code they architect, and takes personal ownership of the systems they ship. They combine deep expertise in AI and distributed systems with strong product instincts, excellent communication skills, and genuine curiosity about data analytics workflows, and they know when to use AI and when deterministic logic is the better answer. This is a high-leverage role at the intersection of data engineering, AI, product impact and technical leadership. Responsibilities: Translate business problems and objectives into actionable AI initiatives; identify opportunities where AI can add value and create roadmaps for implementation with clear milestones and dependencies. Guide the organizational's AI strategy, technology stack, and framework selection. Design production-grade scalable, secure, and efficient AI systems that reason, plan, and act across tools and modalities for data pipelines and applications. Establish enterprise AI reference architectures and reusable components covering data flows, model lifecycle, runtime patterns and integration approaches. Monitor emerging trends in AI and conduct proof-of-concepts (PoCs) to evaluate new technologies. Work closely with engineers and partner teams to build new AI-enabled data pipelines and applications. Evaluate and select the most suitable tools, platforms, and te…