Internal Tooling Engineer - Services Special Projects

At Apple, we build products and services that enrich the everyday lives of millions of people around the world. Our Services team is at the forefront of delivering intelligent, delightful experiences powered by Generative AI — from on-device capabilities to cloud-backed features that work seamlessly across the Apple ecosystem. We are looking for talented developers who are passionate about bringing the next generation of AI-driven platform and self-service tools. Build AI-powered platforms and self-service tools that empower engineers and leadership across the organization to query systems, run analyses, and get actionable insights. You’ll take AI capabilities—such as agents and MCP-based services—from concept to production, ensuring they meet measurable quality standards through robust evaluation pipelines and comprehensive testing before launch. This role also means owning the full technology stack: from data pipelines and streaming integrations that ground services in real production data, to the infrastructure that ensures system reliability, and the dashboards, APIs, and CLIs that enable seamless self-service workflows. Additionally, you’ll contribute to building foundational ML platform components, including model experimentation, inference, and serving pipelines. Your primary customers are other engineers and organizational leaders; your success is measured by their increased velocity and the reliability of the solutions you deliver. Minimum Qualifications: BS in CS, Engineering, or equivalent professional experience. 6 years building production software, including full-stack web applications. Strong proficiency in Python and TypeScript / JavaScript. Hands-on experience with a modern frontend framework (React, Next.js, or similar) for building technical dashboards and tooling. Backend experience with Python frameworks (FastAPI, Flask, Django) and REST/GraphQL API design. Familiarity with containers (Docker), orchestration (Kubernetes), and CI/CD pipelines. Strong product sense for internal-developer ergonomics. Excellent collaboration and communication skills. Preferred Qualifications: Experience building internal developer platforms or productivity tooling at scale. Hands-on with ML lifecycle tooling: MLflow, Weights & Biases, DVC, LangSmith. Familiarity with vector databases, model serving (vLLM, SGLang, Triton), and feature stores (Feast, Tecton). Workflow orchestration (Airflow, Prefect, Temporal). Design instinct — you can ship a UI that engineers actually want to use. Experience with Swift / SwiftUI for native macOS internal tools. Authentication/authorization patterns for enterprise environments.