QE Intelligence - Software Development Engineer - Apple Maps

At Apple Maps, we're not just building world-class location experiences - we're shaping the future of how people explore and navigate the world. The Maps Client Quality Engineering Intelligence (QEI) team applies AI across the full breadth of QE workflows - from test scheduling and triage to coverage analysis and release readiness - to help QE leads and SDETs ship with confidence. We raise quality and velocity at the same time. Our culture is one of deep collaboration, shared ownership, and a belief that the best solutions come from staying close to the people who use them. If you're excited about applying AI to transform how a large quality organization works, we'd love to have you on the journey.

As a member of the Maps Client Quality Engineering organization, you will identify opportunities to apply AI solutions across QE workflows - test planning, automation, triage, analytics, and reporting- and build the platforms that deliver them. You will bridge QE leads who define test strategy and SDETs who build automation foundations, becoming the engineer both groups come to when they need a problem solved. The AI landscape is changing fast; you will help the team stay ahead by evaluating new techniques, prototyping quickly, and knowing when to ship versus iterate.

Strong Python skills with experience building backend services, data pipelines, or APIs.\n\nExperience with web technologies (TypeScript, React/Next.js, or similar frameworks).\n\nProven ability to ship features end-to-end: requirements through deployment and monitoring.\n\nSolid understanding of REST API design, microservices architecture, and CI/CD.\n\nExperience partnering with QE or automation engineers to define tooling needs and architect solutions.\n\nFoundational understanding of AI concepts - LLMs (e.g. Claude), agents, RAG architectures, prompt engineering, and Model Context Protocol (MCP) - with the ability to apply them to real engineering problems.\n\nExposure to or experience integrating AI/ML into engineering workflows (intelligent triage, test selection, knowledge retrieval).\n\nStrong analytical, debugging, and communication skills.\n\nCreative problem-solver who can turn ambiguous asks into concrete deliverables.\n\nBachelor's or Master's degree in Computer Science or equivalent, with 3-6 years of industry experience in software development.

Hands-on experience deploying AI/ML in production settings - shipping models, pipelines, or AI-powered features to real users.\n\nPassion for building clean, reusable tools and contributing to platform evolution.\n\nStrong sense of ownership and drive to improve quality at scale.\n\nBackground in developer tooling, internal platforms, or test automation frameworks (XCTest, XCUI, or similar).\n\nFamiliarity with large-scale engineering platforms (bug tracking, test execution, CI/CD, build systems) and navigating complex enterprise tooling ecosystems.