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Senior Engineering Manager, Applied AI & Agentic Commerce Intelligence
AppleCupertino, California, United StatesSenior$267,800 - $401,70012+ years
Apply Imagine the possibilities here. At Apple, great ideas swiftly transform into exceptional products, services, and customer experiences. We firmly believe that with passion and dedication, you can achieve remarkable things! Every new product, service, or feature we create is the result of collaborative efforts, where each person strengthens the other's ideas. This synergy thrives here because we all strive towards a shared goal: crafting the best customer experiences.
The Channel Sales AI Product Engineering team builds the applied intelligence layer powering Store, Shopping, Learning, and Decision Intelligence experiences used by Apple internal teams, partners, and their customers across 38+ locales — some reaching more than a billion users. We're looking for a Senior Engineering Manager to own this intelligence layer end-to-end: setting technical strategy, leading a multidisciplinary organization spanning applied ML, data science, and product engineering (including frontend and iOS), and delivering the full user-facing experience — not just the intelligence layer beneath it. This is a startup environment inside Apple, with the caliber and scale of Apple's global products, and the product build has direct, measurable business impact.
As a Senior Engineering Manager, you will lead and inspire a team of highly talented and experienced engineers and scientists. You will have strong technical, communication, and people management skills and be responsible for the team's strategy and execution. You'll operate with significant autonomy, represent AI Product Engineering in senior leadership forums, and be expected to translate ambiguous, evolving priorities into a clear technical and organizational narrative — the kind of judgment and polish Apple expects at this altitude.
- Technical & Product Strategy
- Own the Applied AI intelligence layer of the Channel Sales AIML Platform, defining how AI reasoning and domain intelligence are applied across Store, Shopping, Learning, and Decision Intelligence.
- Own the end-to-end product architecture spanning applied intelligence and client experience (iOS, web) — ensuring the intelligence layer and the user-facing surfaces built on top of it form one coherent, high-craft product.
- Translate AI strategy into reusable intelligence capabilities that scale coherently across products and 38+ locales — avoiding product-specific forks or duplicated logic.
- Set and enforce the quality bar for applied intelligence, including correctness, safety, auditability, and global consistency.
- Track the state of the art in agentic AI, LLM reasoning, and planning/tool-use techniques, and translate promising approaches into production-ready designs.
- Executive & Cross-Functional Leadership
- Serve as a strategic thought partner to AI Product Engineering leadership, shaping the platform's vision, priorities, and long-term roadmap.
- Represent AI Product Engineering leadership when needed — using judgment and discretion to unblock decisions in cross-functional and executive forums.
- Communicate strategy, tradeoffs, and risk in a form senior leadership can act on quickly: crisp, narrative-driven, and grounded in business impact rather than technical detail alone.
- Build trust and influence across Channel Sales, AIML, and SWE orgs, often without formal authority.
- Define and lead initiatives addressing the organization's longer-term needs, including workforce planning and organizational transformation.
- Team Leadership
- Lead and grow a multidisciplinary organization spanning applied ML, data science, domain intelligence, and product engineering — including frontend and iOS engineers — responsible for building the actual end-user experiences on top of the intelligence layer.
- Directly manage a team of engineering and applied science managers, in addition to senior ICs — setting their goals, developing their leadership capability, and holding them accountable to the org's technical and craft bar.
- Own both the intelligence and the experience: ensure AI reasoning, product design, and client-side execution come together into a single coherent, high-craft product, not a backend capability handed off to another team.
- Develop senior technical leaders and managers across ML and product engineering disciplines, capable of operating at system scale.
- Foster a culture of accountability, rigor, thoughtful risk-taking, and continuous learning — holding the team to Apple's bar for craft across both intelligence and user-facing experience.
- Streamline processes, tooling, and resourcing across a cross-disciplinary team to move with startup-level speed inside a large organization.
- 12+ years of experience in applied machine learning, decision systems, or large-scale AI systems.
- 5+ years managing high-performing technical teams, including experience managing managers (not just individual contributors) across cross-disciplinary organizations spanning ML/data science and product engineering (e.g., frontend, iOS, or client-side application teams).
- Proven track record leading an AI-powered product from concept through launch at global consumer scale (1B+ users), including the organizational and technical rigor required for phased rollout, reliability, and global performance.
- Hands-on track record shipping ML-powered products or features, ideally involving LLMs and AI agents capable of planning and tool use.
- Demonstrated experience presenting technical strategy and tradeoffs directly to senior/executive leadership, including navigating real-time pushback and ambiguity in the room.
- Experience operating in high-ambiguity, low-guidance environments — defining the plan, not just executing one.
- Strong organizational skills and comfort thriving in a startup environment inside a large organization.
- Bachelor's degree or equivalent experience required.
- Hands-on experience shipping LLM-powered consumer-facing products or features at scale.
- Experience with personalization, recommendation systems, or commerce intelligence.
- Experience with multilingual or global-scale AI deployments.
- Experience managing or partnering closely with native mobile (iOS) and web/Frontend engineering teams to deliver polished, production-grade user experiences.
- Prior experience at Apple or in similarly craft-obsessed, discretion/confidentiality-heavy environments.