Engineering Manager, AI Developer Tools

The Developer Experience team is seeking an Engineering Manager to lead a team building the next generation of AI-powered developer tooling that hundreds of Apple engineering teams rely on daily. You'll hire, develop, and lead engineers who design and ship intelligent agents that transform the software development lifecycle — from initial development through testing, deployment, and beyond. You'll set the technical direction for a portfolio of AI-powered products: coding agents, root cause analysis agents, deployment agents, code review agents, MCP servers, Slack integrations, CLI tools, and APIs that serve both human developers and autonomous systems. Your team will build production-grade AI capabilities, measure their impact through DORA and SPACE metrics, and iterate based on direct user research with engineering teams across Apple. You'll set CI/CD policies and standards that balance velocity with safety, working with cross-functional partners to establish guardrails for AI-assisted deployments at scale. Your team's work will make AI capabilities a seamless, integrated part of how developers build services at Apple. This role requires both hands-on technical depth in agentic AI systems and proven leadership in building high-performing engineering teams. You'll partner with project managers, peer engineering leaders, and senior stakeholders to align your team's roadmap with organizational priorities while maintaining the autonomy to make bold technical bets. - Build, lead, and develop a team of engineers who ship AI-powered developer tools — planning agents, coding agents, testing agents, deployment agents, operations agents, and the APIs and integrations that hundreds of engineering teams depend on daily. - Define and track DORA metrics (deployment frequency, lead time, change failure rate, MTTR) and SPACE metrics (satisfaction, performance, activity, communication, efficiency) to measure and improve developer productivity across Apple. - Set CI/CD policies and standards for AI-assisted development workflows, balancing deployment velocity with safety and compliance requirements. - Drive technical strategy for scalable backend services and APIs in Java and Python that support developer efficiency workflows across Apple. - Conduct user research with engineering teams to identify pain points, validate solutions, and prioritize the roadmap based on measured developer impact. - Evolve platform architectures for reliability, maintainability, and performance at scale, making build-vs-buy decisions and managing technical debt. - Establish engineering excellence standards — code review practices, testing strategies, operational readiness — and foster a culture of quality and continuous improvement. - Recruit, mentor, and retain top engineering talent with expertise in AI agent development and developer tooling. 1+ years of engineering management experience leading teams building backend systems or developer tools. 5+ years of hands-on software engineering experience, with strong fundamentals in Java and Python. Deep familiarity with AI agent frameworks and patterns — LangChain, Claude Agent SDK, Pydantic AI, or equivalent — with the ability to evaluate architectural tradeoffs and guide implementation decisions. Experience defining and using developer productivity metrics (DORA, SPACE, or similar frameworks) to drive measurable improvements. Track record of setting CI/CD policies and infrastructure automation standards for engineering organizations. Experience with databases (relational and/or NoSQL) and scalable service architectures. Excellent communication skills with the ability to influence across organizational boundaries. BS, MS, or PhD in Computer Science/Engineering or equivalent experience. Passion for developer experience and empathy for building tools that empower other engineers. Experience with LLM orchestration patterns, prompt engineering, evaluation frameworks, and responsible AI deployment practices. Familiarity with AI/ML frameworks (e.g., PyTorch, TensorFlow) and LLM libraries (e.g., LangChain, Hugging Face, Anthropic SDK). Experience with Kubernetes for container orchestration and deployment at scale. Experience with messaging systems (e.g., Kafka) and microservices architectures. Track record of building teams from scratch or through significant growth phases. Experience partnering with product management to define tooling strategy and prioritize competing demands across multiple stakeholder teams.

For more details click Job Post.