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Description
This team is responsible for building and maintaining frameworks, systems, and approaches that integrate Xcode with a variety of intelligent tools for developers — including third-party coding agents and large language models. Day-to-day, engineers on the Xcode Intelligence Foundations team work cross-functionally with peers at Apple and our industry partners to build features, troubleshoot issues, and help prototype and conceive the next generation of software development tools. Engineers are expected to actively participate in all aspects of building software — from design and planning through evaluation and long-term maintenance. The transformational opportunities offered by LLMs across all disciplines come with new challenges, ranging from fundamentally new ways of modeling problems to the ethical implications of generative content; candidates for this team should be prepared to grapple with these challenges directly and responsibly. The best candidates for this team are curious, thoughtful, and always put people first.
Minimum Qualifications
3 years experience developing desktop or mobile applications Bachelor’s degree or equivalent experience in computer science or a related field A track record of building thoughtful, polished user experiences. A demonstrated ability to think critically and creatively Instincts for clear problem solving and an ability to discern when a simpler or different approach is needed
Preferred Qualifications
Experience with generative AI concepts and technologies. A clear understanding of the basic elements of a Large Language Model as it exists today, why it can do the things it does, and where it may fall short Familiarity with Swift and Apple’s platforms and SDKs Experience building developer tools or LLM-assisted experiences Strong depth of understanding in one or more of: Performance optimization, API and standards design, compilers and lower-level runtime features, information retrieval structures and algorithms, language tooling and static analysis, or interfaces between probabilistic inference and deterministic software systems
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