Senior Distributed Systems Engineer - Services Special Projects

Apple·Cupertino, California, United States·posted 11d ago · last seen 48m ago

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One of tech's least standardized loops: you interview for a specific team, and every stage belongs to it. Recruiter/hiring-manager screen, one to three 45–60 minute Coderpad coding screens, a system design round shaped by Apple's reliability and privacy constraints, and a behavioral round — then a panel debrief. There is no central question bank; questions map to the team's real stack.

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Description

Summary

At Apple, great ideas turn into phenomenal products, services, and customer experiences at a pace few companies can match. We're looking for an experienced backend engineer to design and build massively scalable, highly available services that power experiences for Apple customers.

Description

As a senior member of the Services Engineering Team, You'll 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. You'll also help evolve 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.

Key Responsibilities

Design and build new features and services with a focus on scalability, responsiveness, fault tolerance, and high availability. Design and build large-scale backend services that are resilient to failures, without breaking downstream consumers. Partnering with search/ranking teams, ML Teams and business teams to ship customer-facing features through performant, well-modeled service APIs. Provide technical guidance and mentorship, fostering a culture of learning and growth.

Minimum Qualifications

Master's degree in Computer Science or a related field 8+ years of professional software development experience building scalable, distributed systems in production 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).

Preferred Qualifications

Self-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.

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