Tools & Frameworks Automation Engineer, Wireless Technologies & Ecosystems

Our team owns the validation, automation infrastructure, frameworks, services, and testing tools that ensure the reliability of wireless technologies across Apple’s ecosystem. We are shifting toward heavily AI-augmented development and solutions, including building and leveraging modern agentic systems powered by large language models to intelligently triage issues, automate root-cause analysis, prioritize bugs/test failures, and drive faster resolutions. We’re seeking a curious, driven engineer who excels at finding and resolving bugs through both manual expertise and AI-assisted approaches, with a strong passion for developing robust tools, automation, and next-gen agentic triage capabilities that scale quality assurance. Minimum Qualifications Bachelor’s Degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience. 10+ years as a Software Development Engineer with proven technical ownership and influence on complex projects. 4+ years designing and architecting tools, frameworks, and automation infrastructure. Strong expertise in investigating, debugging, and triaging complex issues both manually and through modern agentic AI approaches. Solid understanding of automation workflows and CI/CD systems. Preferred Qualifications Thrive in collaborative, cross-functional environments. Demonstrated experience with UI test development (XCUI/Swift) and software validation at scale. Track record of owning and driving complex technical projects to successful delivery. Hands-on experience designing/maintaining CI systems and working in rapid release cycles with tight schedules. Practical understanding of generative AI and experience applying it to development, testing, triage, or automation workflows. Expertise in building or using agentic AI systems for intelligent triage, issue prioritization, root-cause analysis, or autonomous resolution in engineering contexts. Deep knowledge of complex system-level debugging, root-cause analysis, and integrating AI to enhance these processes.