Sr QA Performance Test Engineer

SperiaAtlanta, GA
Hybrid

About The Position

The Sr QA Performance Test Engineer is a senior, hands-on role responsible for designing, executing, and analyzing performance, load, stress, endurance, and scalability testing across enterprise applications and platforms. This role contributes to scaling performance testing capabilities by building repeatable test assets, strengthening CI/CD integration, improving analysis practices, and mentoring other Performance Engineers. The Sr QA Performance Test Engineer works closely with QA, Engineering, Architecture, DevOps, Product, and Program Management to identify performance risks early and drive measurable improvements. The role incorporates AI-assisted techniques to enhance performance analysis, improve scenario realism, and strengthen risk identification across assigned systems.

Requirements

  • Senior, hands-on role.
  • Experience in designing, executing, and analyzing performance, load, stress, endurance, and scalability testing.
  • Experience with enterprise applications and platforms.
  • Experience in building repeatable test assets.
  • Experience in strengthening CI/CD integration.
  • Experience in improving analysis practices.
  • Experience in mentoring other Performance Engineers.
  • Experience working closely with QA, Engineering, Architecture, DevOps, Product, and Program Management.
  • Experience identifying performance risks early and driving measurable improvements.
  • Experience incorporating AI-assisted techniques to enhance performance analysis, improve scenario realism, and strengthen risk identification.

Responsibilities

  • Designing, executing, and analyzing performance, load, stress, endurance, and scalability testing across enterprise applications and platforms.
  • Building repeatable test assets.
  • Strengthening CI/CD integration.
  • Improving analysis practices.
  • Mentoring other Performance Engineers.
  • Working closely with QA, Engineering, Architecture, DevOps, Product, and Program Management to identify performance risks early and drive measurable improvements.
  • Incorporating AI-assisted techniques to enhance performance analysis, improve scenario realism, and strengthen risk identification across assigned systems.
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