Senior Applied AI Engineer, Agent Tools & Capabilities

Summary

Join the team redefining what a deeply personal and integrated assistant can be. As part of the Siri organization, you will help shape one of the world's most widely used AI assistants, powered by our next-generation of Apple Intelligence, with capabilities like personal context understanding and on-screen awareness, built with privacy from the ground up. We extend what Siri can do, connecting it to the apps and services you use and love, defining how the model and the software meet, and building the platform that powers it all. This is a rare opportunity to build at the intersection of cutting-edge AI and human-centered design, shipping technology that is centered around users and their needs.

Description

Join the team defining how next-generation intelligent assistants take action in the real world. As a Senior Applied AI Engineer, you’ll help define how our models reason, plan, and execute across Apple’s vast ecosystem of apps and services. You will develop the core platform, runtime, and API abstractions that make models genuinely effective at scale, powering the next wave of agentic capabilities for Siri and Apple Intelligence.

We’re seeking an individual with a proven track record working at the intersection of models and software, with experience in both systems engineering and applied machine learning. You bring strong developer empathy and API design sensibility to partner closely with the teams behind Apple’s world-class apps, using frameworks like App Intents and real-world developer requirements to drive the evolution of the platform. At the same time, you understand what it takes to make agents fundamentally more capable: crafting the language the model sees, designing tool representations, and building orchestration systems that allow our models to plan and reason through novel capabilities efficiently. You will tackle the demands of scale, ensuring the model behaves reliably and accurately across an enormous action space while keeping latency and inference cost minimal. Your work will focus on engineering the execution layer to be blazing fast across every Apple device — from our most powerful Macs and iPhones to Apple Watch — all while embedding an uncompromising safety, security, and privacy architecture directly into the platform.

This role is an opportunity to push the boundaries of agent effectiveness and own the end-to-end quality story for an assistant used by hundreds of millions of people. You will design realistic evals, diagnose complex failure modes, and bridge the gap between platform infrastructure and foundation modeling to transform state-of-the-art models into dependable, day-to-day capabilities.

Responsibilities

• Develop and optimize the platform and runtime powering Siri under strict latency, memory, and power constraints
• Advance agent capabilities through systematic, data-driven experimentation
• Drive the quality loop from early stage feature development through hillclimbing on data from the field
• Collaborate closely with Apple’s app and frameworks teams to bring their experiences into Siri and use their requirements to shape the platform
• Navigate ambiguity and move fast in a rapidly evolving, frontier AI space

Minimum Qualifications

• Bachelor's degree in Computer Science, Machine Learning, or a related field, with 3+ years of industry experience
• Strong programming skills in languages like Swift, C++, Objective-C, or Python
• Hands-on experience shipping production systems built around LLMs
• Knowledge of agentic systems, including planning, orchestration, and multi-step tool use
• Ability to communicate and deliver in fast-moving, ambiguous environments

Preferred Qualifications

• Experience in prompt engineering, tool representation, or tool retrieval
• Experience designing evals and improving model quality with data
• Familiarity with App Intents or other Apple frameworks
• Strong API design skills and a track record of building platforms for other developers
• MS or PhD in Computer Science, Machine Learning, or a related field