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Salary
≈ $230k – $423k per year (Estimated)
Location
In office (Cupertino)
Seniority
Senior · 8+ years exp
Visa
H-1B filings in 12 months: 6,350 · for this role: 2,996 · green card filings: 37

Confirmed on the employer's own hiring board on Oct 21, 2026. First seen by Alion on Oct 20, 2026. Apple scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Apple is an American multinational technology company founded in 1976 by Steve Jobs, Steve Wozniak and Ronald Wayne, and headquartered in Cupertino, California. It designs and sells consumer hardware including the iPhone, Mac, iPad, Apple Watch, AirPods and Vision Pro, together with the operating systems and silicon that run them. A growing services division built around the App Store, iCloud, Apple Music, Apple TV+ and Apple Pay now contributes a large share of profit, making Apple one of the most valuable companies in the world.

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.

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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