Lead Distributed Systems Engineer - Services Special Projects

Apples Special Services Team is seeking a Lead (Principal) Distributed Systems Engineer to design and build massively scalable, highly available services that power experiences for Apple customers both now and in the future.

In this Lead role, you will build and operate high-throughput, low-latency backend services that ingest, process, and serve data at scale across a range of mission-critical workloads - from real-time transactions to analytics and content delivery. Youll also drive the evolution of a multi-tenant platform, including AI/ML-powered services, by shipping new capabilities, scaling what exists, and applying distributed-systems best practices from design through production.Lead the design and building of new features and services with a focus on scalability, responsiveness, fault tolerance, and high availability. Oversee large-scale backend services that are resilient to failures, without breaking downstream consumers. Lead the partnership with other Apple teams to ensure we ship customer-facing features which are performant, well-modeled service APIs. Be the lead technical guide and mentor for this growing team, fostering a positive culture of learning, growth, and innovation. Lead high-level discussions across Apples ecosystem Masters degree in Computer Science or a related field 15+ years of professional software development experience building scalable, distributed systems in production, with at least 5 in a Principal or Sr. Staff Level role. Experience building, authoring, and operating large-scale, multi-tiered distributed systems and customer-facing web services: including API design, authentication, authorization, scaling for high availability, concurrency, and reliability. Strong understanding of concurrency and multi-threaded programming, fundamental data structures, and efficient algorithm design Strong proficiency in Java; working knowledge of a second systems language (Go, C++) is a plus. Solid OO analysis and design skills. Strong proficiency in application frameworks (Spring boot) Hands on experience with JVM performance tuning and profiling - GC selection/tuning, JFR, async-profiler, heap/thread-dump analysis for low-latency services. Hands-on with async and reactive JVM stacks: Netty, Project Reactor, RxJava, Vert.x, or Micronaut/Quarkus. Rigorous testing discipline with JUnit 5, Mockito, AssertJ, Testcontainers, and contract testing. Hands on experience with build and dependency management with Gradle Deep understanding of transactional consistency models - ACID semantics, with deep knowledge of tradeoffs between relational and NoSQL database technologies Expertise with synchronous and asynchronous network I/O and RPC frameworks (gRPC) Experience building and maintaining CI/CD pipelines (e.g., Jenkins, GitHub Actions, GitLab CI, or similar) for automated testing, build, and deployment of production services. Experience with AWS or GCP and cloud-native tooling (Docker, Kubernetes) in the context of deploying scalable production grade services. Experience with event streaming and queueing systems (specifically Kafka) and stream processing frameworks and high-throughput, append-only write paths for durable, queryable historical records. Hands on Experience of leveraging data storage (Iceberg, Cassandra) and caching technologies (Redis) in Production services Hands on experience with Serialization/schema tooling: Jackson, Protobuf, Avro, and Schema Registry Experience identifying, triaging, and remediating security vulnerabilities in production services (dependency management, secure code review, threat modeling). Full life-cycle development experience for a consumer product, from concept through deployment Proven history of presenting technical and business concepts to Executive LeadershipSelf-motivated, with strong collaboration and communication skills, and experience in a fast-paced, agile environment Experience with machine learning systems, ML frameworks, libraries and algorithms Familiarity with deployment and optimization of Large scale Production grade AI Services that require GPUs in the path of the transaction. Hands-on experience deploying, serving, and optimizing LLMs or ML models directly in the transaction/request path Experience with security and cryptography (e.g., TLS, X.509 certificates) identity and access management protocols (OAuth2/OIDC/SAML), and secure token/session lifecycle management.