Senior AI Enablement Engineering Manager, Apps Team

Summary

The AI Enablement team will be at the forefront of empowering the Apps organization to build, scale and ship more quickly and confidently through AI-powered developer tooling. As the leader, you will drive this high-impact team responsible for evangelism, consultation and working directly with Application Software development teams to optimize and evolve how we build applications — leveraging AI-powered tooling to accelerate workflows, reduce friction, and elevate engineering standards across the organization. This role sits at the intersection of engineering excellence, build, integration, infrastructure, product thinking, and organizational influence.

Description

As the leader of the AI Enablement team, you are responsible for setting direction, prioritizing and planning, and holding the bar for what optimizations get built and why. Day-to-day, you’ll partner with cross-functional stakeholders to identify development/build and integration bottlenecks and determine how to use AI solutions to optimize and transition into scalable platform solutions, while coaching your team to operate with product discipline and engineering rigor. You’ll serve as an internal evangelist for AI-powered developer tooling, shaping culture and capability across engineering organizations— bringing a relentless growth mindset, thriving in ambiguity rather than needing certainty, and staying restless for what’s next rather than settling into the status quo.

Responsibilities

• Lead and grow a team spanning developer consulting and platform functions, balancing technical depth with people development
• Drive a product-minded culture on the team — consistently asking ‘why are we building this?’ before ‘how do we build it?’
• Own the team’s roadmap from ideation through delivery, ensuring alignment with broader engineering and AI optimization
• Partner with senior engineering and operations stakeholders to identify high-leverage developer pain points and prioritize platform investments accordingly
• Partner with cross-Apple leadership teams to maintain visibility into their roadmap and technical direction, channeling relevant learnings back to Apps to prevent duplicative investment
• Evangelize AI developer tooling capabilities internally, building awareness and adoption across engineering teams
• Establish and communicate a clear vision for developer experience and platform reliability that earns organizational trust
• Represent the team in cross-functional forums, presenting strategies, trade-offs, and outcomes with clarity and conviction
• Mentor and develop engineers across consulting and platform support disciplines, fostering a collaborative, high-accountability team environment

Minimum Qualifications

• Demonstrated AI proficiency, with hands-on understanding of how AI tools and platforms fit into modern Application software development workflows, as well as having led the implementation of AI into software development processes. Using AI to build Applications.
• Proven experience leading a platform engineering, developer experience, or software tooling organization as a formal engineering manager or technical lead
• Additionally, minimum 5 years of experience as a SW engineer
• Track record of applying product-minded thinking to infrastructure or developer tooling — making build-vs-buy decisions grounded in developer impact, not just technical possibility
• Strong background in engineering-aware program management, with the ability to understand and navigate the full idea-to-shipped-code lifecycle
• Exceptional communication and presentation skills, with experience influencing senior technical and non-technical stakeholders
• Demonstrated ability to evangelize new technologies or platforms internally, driving adoption and shifting engineering culture

Preferred Qualifications

• Experience specifically in a Platform Engineering Lead or Developer Experience (DevEx) Lead role with direct responsibility for internal tooling ecosystems
• Familiarity with SRE principles, on-call culture, and reliability engineering as applied to internal developer platforms
• Skilled in translating developer productivity metrics and qualitative feedback into compelling strategic narratives for leadership
• Deep expertise in AI/ML developer tooling, LLM integration patterns, or MLOps infrastructure at scale
• Hands-on experience with developer platform technologies such as CI/CD orchestration, internal IDPs (Internal Developer Platforms), or AI-assisted code tools