Senior Software Engineering Manager, Agentic Infrastructure at Apple

Job 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. 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. 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.

Requirements

Must-haves

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.
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.

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

mlai

Platform: apple
Effort: medium