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Full Stack Software Engineer, AI & Data Platforms, IS&T

Apple
Posted 21 hours ago, valid for 19 days
Location

Austin, TX, US

Salary

Competitive

Contract type

Full Time

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Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your work, and there's no telling what you could accomplish.

Description


AI & Data Platforms (AiDP) is IS&T's engine for AI-powered innovation. The team brings together data, application development, and machine learning — including generative AI — along with data services and customer success functions, to help IS&T build solutions more efficiently and streamline the adoption and embedding of generative AI across Apple. As a Full Stack Software Engineer on the team, you'll build the internal web tools and services that turn complex data into products teams across Apple rely on.

Minimum Qualifications


3+ years of software engineering experience spanning frontend and backend systems 2+ years proficiency in TypeScript, React and modern CSS (e.g., Tailwind) 2+ years experience building production backend services in Python 2+ years experience designing and consuming REST, gRPC, or GraphQL APIs 1+ years experience building applications with modern AI tools and agents 1+ years working proficiency in SQL and experience working with large, complex datasets Bachelor's degree in Computer Science, related field, or equivalent practical experience

Preferred Qualifications


Track record shipping data-intensive UIs with complex state, real-time updates, and large-scale data visualization Strong design and UX craft, with the ability to translate ambiguous requirements into polished, intuitive interfaces Experience with cloud platforms (AWS, GCP , or Azure) and container orchestration (Kubernetes) Experience contributing to high-impact projects through cross-functional partnership with product, design, and infrastructure teams Clear communicator who can navigate architectural trade-offs and work effectively across teams



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