Senior Engineering Manager, Agentic AI & Intelligent Reasoning

Apple is where individual imaginations gather together, contributing to the values that lead to great work. Every new idea has the potential to become an extraordinary product, service, or customer experience. The AI, Search & Knowledge Platforms team builds the foundational intelligence powering Siri, Apple Intelligence, Spotlight, Safari, and intelligent experiences across the Apple ecosystem.

We are seeking an exceptional Senior Engineering Manager to lead the engineering organization responsible for Agentic AI and Intelligent Reasoning. This team is building the next generation of AI systems capable of understanding complex user intent, orchestrating multi-step reasoning, retrieving and synthesizing knowledge, and delivering deeply personalized, accurate, and trustworthy experiences. You will lead a world-class organization of machine learning engineers, software engineers, and applied scientists developing agentic AI frameworks, reasoning systems, planning engines, memory architectures, and orchestration platforms that enable Apple's AI experiences to solve increasingly sophisticated user problems while maintaining Apple's industry-leading standards for privacy, reliability, and user trust.

Minimum Qualifications

• MS or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Natural Language Processing, or a related technical field.

• 8+ years of experience leading engineering organizations delivering large-scale AI, machine learning, or distributed systems in production.

• Proven track record of delivering complex AI platforms from research through production at large scale.

• Strong experience in large language models, conversational AI, intelligent agents, reasoning systems, or advanced machine learning platforms.

• Demonstrated success leading cross-functional organizations and defining long-term technical strategy while executing complex engineering programs.

Preferred Qualifications

• Deep expertise in agentic AI architectures, autonomous agents, reasoning systems, planning algorithms, tool use, memory architectures, multi-agent systems, and orchestration frameworks.

• Strong engineering and R&D experience in large language models, Retrieval-Augmented Generation (RAG), long-context reasoning, chain-of-thought optimization, reinforcement learning for LLMs (RLHF, RLAIF), model alignment, and advanced context techniques.

• Experience building systems for multi-intent understanding, multi-hop reasoning, deep research, evidence synthesis, complex workflow execution, and personalized AI experiences.

• Experience designing scalable evaluation systems for reasoning quality, factuality, grounding, personalization, safety, agent reliability, and user experience.