Senior Software Engineering Manager, Agentic Infrastructure

Were 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. 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.Build, mentor, and manage an inclusive organization of high-performing engineers. Dedicate time to fostering talent, driving hiring and onboarding, managing performance, and prioritizing overall team health and growth paths. Define the strategic vision and technical roadmap for agentic workflows and developer experience. Drive the execution of complex, multi-year projects end-to-end, balancing rapid iteration with long-term architectural stability. Partner closely with cross-functional product and cloud teams to enable delivery of seamless, secure, and delightful AI experiences. Foster a culture of engineering excellence and build for scale and performance, focusing on system reliability, scalable cloud architecture, observability, throughput and latency, cost efficiency, and robust evaluation metrics. Champion the adoption of generative AI tools and agentic workflows across the broader software organization to improve developer productivity and software quality. Spot problems before they occur, proactively resolve cross-functional bottlenecks, and present your teams work to executive leadership to advocate for resources and technical direction. Champion the security and privacy of user content, ensuring the team consistently applies secure-by-design and privacy-by-design principles in all architecture and delivery.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. Bachelors, Masters, or equivalent professional experience in Computer Science, Computer Engineering, or a related field.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.