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# Performance Team within Developer

- **Company:** Apple Inc.
- **Location:** Santa Clara, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Concurrency Controls, Continuous Integration, Data Structures, Distributed Systems, Domain Name System (DNS), Hypertext Transfer Protocols (HTTP), Load Testing, Regression Analysis, Network Protocols, Software Engineering, TCP/IP, Workflow Management Systems, Siri, Backend, Kubernetes, Information Technology
- **Published:** October 3, 2026
- **Apply:** https://www.dice.com/job-detail/d45d8a85-a222-46a1-a60c-ce820affc115

## About the Role

10+ years of experience in software development, including designing, building, and operating large-scale distributed systems and backend infrastructure

Solid understanding of networking protocols (e.g., TCP/IP, DNS, HTTP) and their application in large-scale systems

Strong software engineering fundamentals in data structures, algorithms, and system design

Excellent communication and collaboration skills to work effectively with cross-functional teams

BS, MS, or Ph.D. in Computer Science or a related field, or equivalent experience

Preferred Qualifications

Statistical/analytical experience projecting how dev-environment results map to production behavior (regression analysis, capacity modeling)

Hands-on experience designing load test frameworks: traffic capture/replay, configurable load shapes, concurrency control

Experience with observability tooling for root-causing performance regressions

Familiarity with Kubernetes, workflow orchestration and CI/CD pipelines for automating test infrastructure

## Description

We build the infrastructure that lets developer teams across Search test, measure, and validate the performance of features before they reach billions of Siri users. Our platform captures and replays production-scale traffic so developers can load-test changes in a dev environment and trust that the results are indicative of production behavior. We apply statistical analysis to model how latency, throughput, and resource usage shift from dev to production, helping teams catch performance regressions before they ship. You'll have the opportunity to work with systems processing massive volumes of traffic and results data, with a scale and complexity few teams encounter.