Performance Test Engineer

About the Role:

We’re looking for a Performance Test Engineer who thrives at the intersection of engineering precision and AI-driven innovation . In this role you’ll design execute and evolve our performance testing ecosystem — blending the rigor of traditional testing with the intelligence of automation and agent orchestration.

You’ll work closely with engineering DevOps platform and AI teams to simulate real-world conditions identify bottlenecks and ensure our systems are highly scalable resilient and efficient — delivering seamless experiences to millions of users globally.

What You’ll Do:

Core Performance Engineering

• Design and execute comprehensive performance test strategies — Load Stress Soak Spike Scalability and Endurance testing.

• Develop and maintain performance scripts using tools such as JMeter Gatling LoadRunner Locust or k6 .

• Simulate realistic user traffic and workload models for distributed systems.

• Perform root cause analysis across application API database and infrastructure layers.

• Define and maintain performance baselines SLAs and SLOs .

• Integrate performance tests into CI/CD pipelines for continuous validation.

Advanced & AI-Driven Performance Testing

• Build AI-driven performance analysis frameworks using pattern recognition and anomaly detection.

• Develop custom test agents/orchestrators using MCPs to simulate large-scale multi-node workloads.

• Implement self-healing test systems that adapt dynamically to environment changes.

• Use ML models to predict performance degradation and proactively optimize systems.

• Automate root cause detection with AI-assisted observability insights.

Monitoring & Insights

• Use observability tools ( Grafana Prometheus Datadog New Relic AppDynamics ) to monitor and analyze performance metrics.

• Create visual dashboards to communicate trends and optimization opportunities.

• Collaborate with SRE and development teams for end-to-end performance tuning.

Collaboration & Process

• Partner with engineering QA and platform teams early in the SDLC to define performance goals.

• Conduct post-release reviews and contribute to testing standards and best practices.

What You’ll Bring:

• 5+ years of experience in performance testing for large-scale distributed systems.

• Strong programming skills in Python Go or JavaScript/TypeScript .

• Hands-on with modern testing tools ( JMeter Gatling Locust k6 LoadRunner ).

• Expertise in performance metrics — latency throughput error rate concurrency resource utilization .

• Experience integrating with CI/CD (Jenkins GitHub Actions Azure DevOps).

• Deep understanding of microservices containers (Docker Kubernetes) and distributed architectures.

• Skilled in analyzing logs metrics and traces for performance bottlenecks.

Bonus Points For

• Experience with AI-assisted testing anomaly detection or AIOps .

• Familiarity with chaos engineering tools (Gremlin LitmusChaos).

• Exposure to AWS Azure or GCP environments.

• Database performance tuning and caching strategies.

• Contributions to open-source testing or AI performance frameworks .