Performance Test Engineer

The Performance Test Engineer will be a core member of Five9's Performance Engineering team, responsible for designing, building, and executing performance tests across our cloud contact center platform. The ideal candidate has hands-on experience creating realistic workload models, running load and stress tests, and turning test results into clear, actionable findings for development teams. They will apply modern AI-assisted tooling to accelerate test analysis and anomaly detection, helping Five9 deliver consistently fast and reliable product experience.

• →Design, develop, and maintain performance test scripts and scenarios using tools such as k6, Gatling, JMeter, or Python
• →Build and maintain realistic workload models that accurately represent production traffic patterns and user behavior
• →Define and document performance test objectives, entry/exit criteria, and service level objectives (SLOs)
• →Execute a range of test types including baseline, load, stress, soak, spike, and scalability tests
• →Analyze test results to identify bottlenecks, regressions, and areas of concern; produce clear written findings and recommendations
• →Collaborate closely with developers, QA engineers, and architects to share results and support remediation efforts
• →Set up and maintain performance test environments and test data in alignment with production configurations
• →Integrate performance tests into CI/CD pipelines to enable continuous performance validation
• →Define and configure monitoring dashboards and alert thresholds using observability platforms (e.g. Datadog, Grafana, Prometheus)
• →Triage performance-related defects and contribute to root cause analysis investigations
• →Maintain performance test documentation, test plans, and results archives
• →Leverage AI-assisted tooling for automated anomaly detection, intelligent baselining, and accelerated result analysis
• →Use AI/ML-powered AIOps platforms to identify trends, predict regressions, and reduce mean time to detection (MTTD) for performance issues

• 4–7 years of hands-on experience in performance testing or performance engineering
• Practical experience writing and maintaining test scripts in one or more of: k6, Gatling, JMeter, or equivalent
• Solid understanding of performance test types and when to apply them (load, stress, soak, spike, scalability)
• Experience defining workload models and translating production metrics into test scenarios
• Proficiency with application performance monitoring tools (e.g. Datadog, New Relic, Grafana, Prometheus, AppDynamics)
• Ability to interpret test results and thread/heap dumps, identify bottlenecks, and communicate findings clearly to technical and non-technical stakeholders
• Experience integrating performance tests into CI/CD pipelines (e.g. Jenkins, GitLab CI, GitHub Actions)
• Scripting or programming skills in at least one language (Python, JavaScript/Node.js, Java, or Groovy)
• Familiarity with AI/ML concepts applied to testing: anomaly detection, intelligent baselining, AIOps, or LLM-assisted diagnostics
• Experience testing web applications and APIs (REST, gRPC, WebSocket) under realistic concurrency
• Strong written and verbal communication skills; ability to present findings and drive discussions with engineering teams

• Experience testing VoIP, real-time communications, or contact center platforms
• Familiarity with containerized test execution environments (Docker, Kubernetes)
• Exposure to chaos engineering practices (e.g. Chaos Monkey, Gremlin) as a complement to performance testing
• Experience with AI observability or AIOps tools (e.g. Dynatrace Davis AI, Datadog Watchdog, Arize)
• Knowledge of distributed tracing tools (e.g. Jaeger, Zipkin, OpenTelemetry) for request-level performance analysis