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Salary
≈ $241k – $493k per year (Estimated)
Location
In office (Seattle)
Seniority
Senior · 10+ years exp
Visa
H-1B filings in 12 months: 6,350 · for this role: 304 · green card filings: 37

Confirmed on the employer's own hiring board on Oct 24, 2026. First seen by Alion on Oct 24, 2026. Apple scores A on the Alion truth index.

Overview
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Apple is an American multinational technology company founded in 1976 by Steve Jobs, Steve Wozniak and Ronald Wayne, and headquartered in Cupertino, California. It designs and sells consumer hardware including the iPhone, Mac, iPad, Apple Watch, AirPods and Vision Pro, together with the operating systems and silicon that run them. A growing services division built around the App Store, iCloud, Apple Music, Apple TV+ and Apple Pay now contributes a large share of profit, making Apple one of the most valuable companies in the world.

We're a team at Apple building the next generation of Private Cloud Compute inference and agentic services. Our work sits at the intersection of cloud services, machine learning, software experiences, and future Apple silicon. We deliver the server software that powers Apple Intelligence. We are seeking a deeply experienced software engineering manager to help drive our technology roadmap and software delivery.

Description

In this role, you will lead and grow a highly talented engineering organization responsible for designing and building agentic systems and the developer experiences around them. The work encompasses design of the core agentic architecture, the integration of various cloud services, and developer tooling. You will partner closely with cross-functional leaders across software experiences, ML research, hardware, system software, security, privacy, and SRE to define technical strategy and deliver production-grade systems running in the cloud. As a senior leader, you will not only guide complex technical architecture decisions but also shape the organizational culture, drive engineering excellence, and influence how AI-assisted workflows are adopted across the broader Apple ecosystem. You will be responsible for scaling successful prototypes into foundational production systems that the broader organization depends on. This position requires a self-motivated individual with strong technical depth, exceptional people management skills, and the ability to navigate ambiguity in a fast-paced, startup-like environment.

Minimum Qualifications

10+ years of engineering management experience, with a proven track record of delivering complex, large-scale engineering projects across multiple teams or organizations.

Solid technical foundation in software engineering, distributed systems, and cloud infrastructure, with an ability to engage deeply with system design trade-offs.

Demonstrated experience building and scaling developer tools, ML infrastructure, or AI systems from concept to production.

Exceptional communication and interpersonal skills, with high emotional intelligence and the ability to influence across all levels, from executive partners to individual contributors.

Demonstrated ability to operate effectively in ambiguity and handle rapidly shifting priorities without losing trust or execution discipline.

Bachelor's, Master's, or equivalent professional experience in Computer Science, Computer Engineering, or a related field.

Preferred Qualifications

Strong working proficiency and conceptual understanding of generative AI, foundation models, and agentic workflows, with hands-on experience bringing AI systems to production at scale.

Experience leading organizations through periods of significant growth or technical transformation, including building and evolving team structures to match scaling demands.

Strong analytical and data-driven mindset, with a genuine interest in software evaluation and using metrics to drive product and architectural decisions.

Experience with Private Cloud Compute, on-device/cloud ML inference pipelines, or Apple silicon-adjacent infrastructure.

Familiarity with secure-by-design and privacy-by-design principles as applied to cloud-based AI services.

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