Performance Engineer

Confirmed live in the last 24 hours

Apple

Singapore

On-site

Posted February 12, 2026

Job Description

Summary

Do you love working on highly scalable and secure distributed applications? Does the idea of fast-paced environment make your heart leap? Do you want your technical abilities to be challenged every day and for your work to make a difference in the lives of millions of people? If so, the Product Engineering Systems group is looking for dedicated hands-on Performance Engineer who are not afraid to share knowledge, think creatively, and question assumptions. Join us to do the best work of your life with a welcoming, diverse, and hard-working group of engineers. Bring passion and dedication to the job, and there’s no telling what you could accomplish!

Description

A good fit candidate for this role would demonstrate a strong passion for delivering systems that are fast, efficient, and scalable at every layer. The candidate will have a deep curiosity to understand how applications behave under load, identify bottlenecks across infrastructure, databases, and code paths, and optimize them for peak performance. They should be comfortable designing and executing large-scale performance tests, analyzing complex datasets to uncover inefficiencies, and partnering with engineering teams to drive measurable improvements. A strong instinct to automate performance validation, visualize metrics, and translate technical insights into actionable outcomes is key to success in this role.

Minimum Qualifications

5+yrs of experience working in large-scale distributed systems, collaborating effectively with Development, QA, SRE, and DevOps teams to define and achieve performance goals. Strong programming and scripting skills in Python, Java, or SQL, with a focus on automating performance testing, analysis, and data-driven optimization. Proven expertise in load, stress, and scalability testing using tools like JMeter, and experience with profiling Java applications to identify and resolve performance bottlenecks. Hands-on experience with performance diagnostics and monitoring using tools such as AppDynamics, including heap/thread dump analysis, GC tuning, and metrics interpretation. Practical knowledge of capacity planning and forecasting, ensuring infrastructure and applications scale efficiently under varying workloads.

Preferred Qualifications

Deep understanding of multi-tier software architectures and how data flows across front-end, mid-tier, messaging, and back-end layers. Familiarity with observability and monitoring tools (e.g., Prometheus, Grafana, Splunk) to correlate performance metrics with system health. Experience with CI/CD integration for performance validation and maintaining regression performance suites. Exposure to capacity planning and scalability modeling, using historical data to predict and optimize resource utilization. A self-driven, detail-oriented engineer with curiosity for emerging performance optimization techniques, including automation and ML-based anomaly detection.