Senior Engineering Program Manager, ASE Central Quality - Private Cloud Compute

The people here at Apple dont just create products - they create the kind of wonder thats revolutionized entire industries. Its the diversity of those people and their ideas that inspires the innovation running through everything we do. Do you believe generative AI has the power to change how we live, work, and interact - and that privacy and security must never be sacrificed in that pursuit? Do you thrive in fast-paced, ambiguous environments and enjoy working across complex, high-stakes technical systems? The Central Quality Engineering Program Manager for Private Cloud Compute (PCC) drives the quality backbone of one of Apples most technically ambitious infrastructure efforts - the systems powering Apple Intelligence. This role sits at the intersection of software engineering, Quality, SRE, and ML/inference release engineering, driving the test strategy, QA sign-off process, and readiness required to ship PCC with the quality and trust Apples customers expect. Youll move fluidly between deep technical detail - build pipelines, staged rollouts, distributed systems - and executive-level communication, building relationships across an organization where the teams you depend on are spread throughout the company. In this role, youll work closely with Engineering, Quality, SRE and ML build/release teams to define and continuously improve how PCC software and infrastructure are validated before they reach production. This includes the build and staged-rollout pipeline for large language models running on PCC, model weight updates across OS and PCC release trains, and the datacenter/Apple Silicon platform validation that underpins the service. You will drive cross-functional programs across teams of highly skilled engineers and program managers - providing direction, fostering collaboration, and holding the bar for quality outcomes. You must be comfortable operating independently in new and unfamiliar domains - quickly building competence in evolving frameworks as well as PCCs own privacy and security architecture, to inform your work. Success requires breaking large, ambiguous problems into manageable pieces, leveraging subject-matter experts across Foundation Models, AIML, evals, and SRE, and adapting your plan as understanding evolves. Strong communication is essential to your credibility: you must synthesize complex technical issues into clear points, tailor communication to different levels of seniority, write clearly, deliver effective presentations, and run large, high-stakes meetings - including incident postmortems when releases dont go as planned.Own the end-to-end Quality Engineering program lifecycle for Private Cloud Compute - facilitating cross-functional coordination and breaking down complex program goals (PCC software releases, LLM/model rollouts, Apple Silicon datacenter integration) into manageable milestones. Act as the primary point of contact and strategic subject-matter expert for "all things QA" on assigned PCC initiatives. Partner with engineering, SRE, and ML build/release teams to identify critical use cases and define comprehensive End-to-End (E2E) test coverage across the PCC software, model release, and infrastructure stack. Own and manage the QA sign-off process end-to-end for PCC releases - including staged rollouts of models and software across OS and PCC release trains - driving critical go/no-go decisions and ensuring production readiness. Drive continuous status tracking and deliver clear, audience-tailored reporting to stakeholders at all levels, from individual engineers to senior leadership. Support and guide the creation of quality standards, testing protocols, and documentation specific to PCC. Establish and track known risks and dependencies across hardware, software, and cross-org partners, escalating and resolving blockers proactively - including leading or supporting incident response and retrospectives for release issues. Define and drive functional test strategy across core PCC components - including request routing, node attestation, inference serving, and API/service surfaces - ensuring functional correctness before code and model changes progress to staging and production.6+ years of experience as a Program Manager / Technical Program Manager / QA Lead / SW Architect / SW Engineer, with a track record of leading complex, cross-functional software programs Outstanding written and verbal communication and presentation skills, adaptable to all levels of an organization Excellent stakeholder leadership skills, with demonstrated ability to influence and collaborate across functions without direct authority Strong analytical and structured problem-solving skills - able to deconstruct ambiguous, complex problems, resolve conflicts, and lead teams to solutions Ability to understand technical systems and translate technical constraints into business impact and vice versa Demonstrated ability to build strong, trust-based relationships across a large, distributed organization Self-starting, self-motivated, self-directed, and comfortable operating with minimal oversight in ambiguous environments B.S. or M.S. in Computer Science, Information Systems, or equivalent practical experience Experience partnering with SRE, infrastructure, or cloud/datacenter engineering teams on large-scale distributed systemsExperience validating ML or LLM workloads running on hardware accelerators (GPUs, NPUs, or Apple Silicon) in a cloud or datacenter environment Familiarity with build/release pipelines for large-scale systems, including model weight management and staged rollouts across release trains Experience with large-scale cloud infrastructure programs, including familiarity with Kubernetes or comparable orchestration platforms Experience owning or supporting incident response and retrospectives for production release issues A track record of managing company-wide, cross-functional programs for privacy-critical or security-critical cloud and AI infrastructure at scale, comparable in complexity to Private Cloud Compute Experience at the hardware-software boundary in a private cloud, hyperscale datacenter, or edge compute environment