Senior Engineering Program Manager, Lead , Service Special Projects

Apple•Cupertino, CA

About The Position

This is a hands-on, lead-level role for a seasoned program manager to launch and manage a large, technically deep, multi-year engineering program. The role connects engineering, research, design, and business functions, translating an ambitious vision into a coordinated, measurable plan and driving it through delivery. The position owns end-to-end program management for a cross-functional initiative spanning client software, backend services, large-scale data systems, applied machine learning, evaluation, tooling, and platform engineering. The Senior Engineering Program Manager is accountable for the plan of record—including roadmap, milestones, dependencies, risks, and executive narrative—and for the operating cadence that keeps teams aligned. The role requires technical fluency to participate in architectural reviews and scoping discussions, read designs, ask incisive questions, and communicate technical discussions accurately to leadership. The role identifies program drift and drives corrective action. In addition to managing workstreams, the lead shapes program-management practices by mentoring junior EPMs, standardizing progress tracking, and improving planning and communication.

Requirements

15+ years of experience developing program plans and managing complex, cross-functional engineering programs in a technical product environment.
At least 3 years in a lead- or principal-level capacity.
At least 5 years leading AI-first programs end to end, where core product value is delivered by machine-learning or large-language-model systems and planning, scoping, and quality are tied to model behavior and evaluation.
Demonstrated experience managing programs end to end across multiple engineering disciplines, including client, services, data, applied ML, platform, and tooling.
Strong technical depth, including the ability to read engineering design documents, follow architectural discussions across disciplines, and reason independently about trade-offs, dependencies, and risks.
Working literacy with the modern AI stack, including model training and evaluation lifecycles, offline versus online metrics, data pipelines, latency and cost trade-offs, and the distinction between research results and production-ready capabilities.
Exceptional written and verbal communication skills, including experience writing concise executive updates and delivering technical narratives to senior leadership.
BS in Computer Science, Engineering, or a related technical field, or equivalent experience.

Nice To Haves

Advanced degree.
Experience building and owning a credible plan of record—including roadmap, milestones, dependencies, and critical path—for programs with dozens of engineers and multiple partner teams.
Experience taking AI/ML capabilities from research prototype through evaluation, hardening, and production launch, with explicit quality bars and rollback criteria.
Experience identifying risks early, developing mitigation strategies, and resolving conflicts across senior technical stakeholders.
Ability to create clarity amid ambiguity while scope, requirements, and priorities are forming.
Ability to track many parallel workstreams in real time.
Experience influencing and aligning teams without direct authority, including senior engineers, architects, applied researchers, and cross-functional leaders.
Experience establishing durable operating rhythms, such as planning cycles, review cadences, escalation paths, and post-mortems.
Experience presenting technical status, trade-offs, and recommendations to executive audiences with precision and honesty.

Responsibilities

Own end-to-end program management of a large-scale, cross-functional engineering initiative.
Create and maintain the plan of record, including the roadmap, milestones, dependencies, risks, and executive-level narrative.
Establish and run an operating cadence that aligns teams on expectations, timing, and rationale.
Participate effectively in architectural reviews and technical scoping discussions; read design documents and ask informed questions.
Translate technical discussions into clear, accurate summaries for leadership.
Identify program drift early and drive corrective action.
Mentor more junior Engineering Program Managers, standardize progress tracking, and improve planning and communication practices.
Build and own program plans, including critical paths, for initiatives involving multiple engineering and partner teams.
Manage risks, mitigation strategies, and conflict resolution across senior technical stakeholders.
Establish planning cycles, review cadences, escalation paths, and post-mortems that scale with the program.
Present technical status, trade-offs, and recommendations to executive audiences.