Engineering Manager, Private Cloud Compute Inference Routing

At Apple, iCloud Platform Engineering builds the server stack behind Push Notifications, iMessage, FaceTime, iCloud, iCloud Private Relay and Private Cloud Compute (PCC), the backbone of Siri AI and Apple Intelligence. We are looking for an Engineering Manager to lead PCC inference routing. These systems send every inference request to the right compute across a global, multi-region fleet, while keeping latency low, availability high and PCC’s privacy guarantees intact.

This is a technically grounded leadership role for someone who thrives at scale, can bring clarity to complex and fast-changing environments, and is energized by building both systems and teams. You’ll guide architectural direction, scale operational practices and develop the engineers and leaders who will shape how Apple delivers cloud inference., Routing LLM inference at Apple’s scale takes systems that adapt to changing demand, available capacity and failures while keeping latency low and accelerator utilization high. As the fleet grows across regions and cells, routing must account for capacity and health across the whole fleet, not just a single site. PCC adds a basic architectural requirement: request content stays encrypted outside trusted compute nodes. You’ll lead the design of routing and scheduling strategies within this privacy model. Together with inference and security teams, you’ll evaluate techniques such as cache-aware request placement and prefill/decode disaggregation. Your scope includes the inference AI gateway layer, where requests are authenticated, metered, prioritized and streamed back to clients, all without exposing request content.

This work has broad reach. Every improvement to routing makes Siri AI and Apple Intelligence faster and more reliable, and makes better use of Apple’s inference capacity. In your first year, you’ll be expected to grow a high-performing organization, set a clear technical roadmap, and measurably improve routing latency, availability and fleet utilization.

Extensive software engineering experience with a demonstrated track record of leading teams that design, build, and operate large-scale distributed systems in production environments-whether through direct management, indirect oversight, or a combination thereof

Proven ability to recruit, develop, and retain high-performing engineers and leaders

Experience delivering API gateways (preferably inference AI gateways), request routing, load balancing, scheduling, or traffic management systems at scale

Expertise of LLM inference serving, including request routing, KV-cache placement and reuse, prefill/decode disaggregation, and the tradeoffs between latency, throughput and accelerator use

A record of shipping highly reliable systems in high-availability environments, including leading incident management, on-call and reliability practices

Strong technical depth: capable of contributing meaningfully to architectural and design discussions with senior engineers, with a server development background in Java, C/C++, Go or Swift

Ability to drive alignment and execution across teams in complex, matrixed environments

Bachelor’s degree in an engineering discipline or equivalent professional experience

Preferred Qualifications

Proven leadership in developing LLM inference serving or routing platforms (e.g., llm-d, NVIDIA Dynamo, vLLM, SGLang, or managed inference services)

Experience building or running inference AI gateways and their core behaviors: token-based rate limiting and usage metering, multi-model routing with fallback, retries and circuit breaking, and streamingresponse handling

Track record of scaling teams and organizations during rapid growth while maintaining top-tier hiring and engineering standards

Experience delivering capacity tiers, reservations or QoS for high-volume workloads, and improving accelerator utilization through cross-region, capacity-aware routing

Understanding of privacy-preserving system design: TLS, X.509, key management, Oblivious HTTP, remote attestation

Experience designing and maturing observability practices, including SLO/SLI frameworks, distributed tracing and on-call culture

Experience with container orchestration systems such as Kubernetes

Demonstrated ability to build psychologically safe, high-trust team environments that attract and retain top talent

Experience formulating multi-year roadmaps in collaboration with product, research, and senior leadership within large organizations that prioritize quality and reliability