Senior Software Engineer, Private Cloud Compute Inference Routing

Apple is looking for a senior software engineer to build the next generation of inference routing for Private Cloud Compute, the backbone of Siri AI and Apple Intelligence. Youll design distributed systems that direct inference requests across a global fleet of inference servers, balancing latency, availability, and compute efficiency while preserving PCCs privacy guarantees. Your work will directly shape how reliably and efficiently Apple delivers cloud inference at scale.

Youll join iCloud Platform Engineering team. We build the server stack behind Push Notifications, iMessage, FaceTime, iCloud, iCloud Private Relay and Private Cloud Compute. Our internet scale distributed systems deliver real-time experiences with very low latency and very high availability. They reach hundreds of millions of users across a billion devices worldwide and help them connect and share their lives securely and privately. Our work spans identity, messaging, queueing, presence, routing, relays, developer APIs and much more. Were a small, highly collaborative team with a large impact. Routing LLM inference at Apples scale requires systems that adapt to changing demand, available capacity, and failures while maintaining low latency and high utilization. PCC adds a fundamental architectural requirement: request content remains encrypted outside trusted compute nodes. Youll develop routing and scheduling strategies within this privacy model, working with inference and security teams to evaluate techniques such as cache aware request placement and prefill/decode disaggregation.

Youll design system architectures, specify custom network protocols and write high performance code. Youll also build scaling strategies for services used by hundreds of millions of people. Our team is small and highly visible, so your chances to make an impact are wide open. If you take opportunities like that and run with them, youll enjoy working here.

Youll own technical decisions from early design through production, using benchmarks and operational evidence to evaluate tradeoffs. Youll work closely with model serving, infrastructure, security, and SRE engineers to turn new inference requirements into reliable routing capabilities.Design, build, and operate PCCs inference routing and request scheduling services, including global traffic management, capacity aware request placement, load balancing, and failover. Develop adaptive routing strategies that respond to changing demand, fleet health, and available compute capacity while maintaining latency and availability objectives. Build admission control, prioritization, and overload management mechanisms that keep the service responsive and allocate capacity fairly across competing workloads. Partner with model serving and infrastructure teams to evaluate and develop routing strategies for prefill/decode disaggregation and cache locality optimizations within PCC's privacy architecture. Design network protocols and implement high-performance server software for inference request dispatch and response streaming. Define performance metrics and benchmark routing strategies under realistic workloads, using queueing delay, request latency, throughput, and fleet utilization to guide improvements. Own projects from architecture through production rollout, partnering with Siri AI, Apple Intelligence, infrastructure, security, and SRE teams to deliver new capabilities and improve reliability.3+ years of professional experience designing, building and operating large distributed systems in production Server development in Java, C/C++, C#, Go or Swift Knowledge of LLM inference serving, including inference request routing, KV-cache placement and reuse (e.g., prefix-aware routing), prefill/decode disaggregation, and the tradeoffs between latency, throughput and accelerator use Experience with network protocols, application level networking and client-server architectures, including request routing, load balancing or scheduling at scale Experience benchmarking, debugging and tuning the performance of distributed systems, plus knowledge of Unix system internals Experience with cloud deployment and observability technologies such as Kubernetes Bachelors degree in an engineering related field or equivalent experienceExperience building LLM inference serving or routing systems such as llm-d, NVIDIA Dynamo, vLLM, SGLang or similar Familiarity with KV cache aware routing, prefix caching, prefill/decode disaggregation and accelerator capacity placement Experience with TLS, X.509 certificate evaluation or other secure protocols, and awareness of recent developments in standard protocols Understanding of cryptographic protocols, encryption, key management and privacy-preserving system design (e.g., Oblivious HTTP, remote attestation) Experience leading a substantial engineering project from design through production, resolving technical tradeoffs and coordinating across teams. Ability to explain technical tradeoffs, collaborate across engineering teams, and make progress on problems with incomplete requirements.