Performance QA Engineer (JCP Core)

JetBrains is a company founded in 2000 focused on creating effective developer tools. The JetBrains Cloud Platform team develops a cloud-based service for managing JetBrains products and services, emphasizing AI-powered development tools adoption. The JCP service provides centralized management, usage-based billing, and visibility into AI consumption patterns.

• 5+ years of experience in performance testing or engineering.
• Strong hands-on experience with at least one major performance testing tool such as K6, JMeter, Gatling, Locust, or LoadRunner (code-based tools preferred, git knowledge required).
• Solid programming or scripting skills in Java, Python, JavaScript/TypeScript, or Go.
• Strong understanding of distributed systems, API performance, databases, caching, and networking fundamentals.
• Proven ability to analyze performance metrics, identify bottlenecks, and recommend improvements.
• Experience testing high-traffic or mission-critical applications.
• Strong analytical skills and ability to communicate technical findings clearly.
• Proficiency in English, both written and spoken.

Nice to have:

• Experience with observability platforms such as Prometheus, Grafana, and Elastic.
• Experience with containerized and cloud-native environments including Docker, Kubernetes, and AWS/GCP/Azure.
• Familiarity with event-driven systems, streaming platforms like Kafka, and microservice architectures.
• Knowledge of CI/CD automation tools such as TeamCity and GitHub Actions.

• Design, develop, and maintain automated performance test suites for complex distributed systems.
• Identify system bottlenecks, conduct root-cause analysis, and partner with engineering teams to implement remediation strategies.
• Generate high-quality performance reports with actionable recommendations and communicate findings to both technical and non-technical stakeholders.
• Work closely with cross-functional development teams to identify performance-critical components and define SLAs, performance criteria, and workload models.
• Design and enhance frameworks for performance test execution, test results collection, analysis, visualization, and reporting.
• Integrate performance testing into CI/CD pipelines.