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Description
Join our Fleet Operations Engineering Organization, dedicated to ensuring infrastructure excellence across Apple. Our mission is to build a healthy, stable, and compliant environment that empowers our internal teams — and data is at the heart of how we do it. This role sits at the exciting intersection of data engineering and generative AI — you'll explore and apply LLM-based tooling, autonomous agents, and modern AI frameworks to make our workflows smarter and more impactful. As a Software Engineer focused on Data and Intelligence, you will design, build, and operate the data workflows and analytical systems that give our team and partners clear visibility into the health of Apple's infrastructure fleet. You'll contribute to Python pipelines, connect systems through APIs, and surface actionable insights through compelling dashboards and web-based tools. You'll develop a full-stack sensibility to your work which makes data and insights accessible to the teams who need them most. If you are curious, data-driven, and energized by building systems end-to-end — from database to dashboard to deployed web app — you will find a meaningful home on our team.
Minimum Qualifications
Software engineering experience with a focus on data engineering, full-stack or backend development Foundational proficiency in SQL and Python Experience consuming and integrating with APIs Strong curiosity and a growth mindset — comfortable approaching new technologies from a place of exploration and experimentation
Preferred Qualifications
Knowledge of programming languages such as Java, Swift, or Go Experience building full-stack internal tools that combine a clean UI with data-rich backends Familiarity with Generative AI and LLM concepts, including prompt engineering, retrieval-augmented generation (RAG), MCP (Model Context Protocol) Experience with cloud-based deployment and observability tooling (e.g., Docker, AWS, GCP, or Azure) Ability to thrive in a highly collaborative, cross-functional environment with a sense of shared ownership A Bachelor’s degree or Equivalent experience/knowledge in Computer Science, Data Science, Machine Learning, or a related quantitative discipline
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