JPMorgan Chase—Software Engineer III - Performance Engineer

Job description

Description: We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer III - Performance Engineer (Playwright, JMeter) at JPMorgan Chase within the Commercial & Investment Bank, you'll serve as a Performance Test Engineer to design, build, and execute performance and reliability testing for critical applications and services. This role blends hands-on performance engineering (load, stress, endurance, scalability) with test automation, including Playwright-based automation experience, to improve quality, resilience, and customer experience across our platforms. Job responsibilities - Design and execute load, stress, spike, soak/endurance, and scalability tests for web applications and APIs. - Develop and maintain performance test scripts using Apache JMeter, including parameterization, correlation, assertions, timers, and test data management. - Execute and manage tests at scale using BlazeMeter (or comparable platform), including distributed runs, scheduling, and reporting. - Leverage Playwright (TypeScript/JavaScript) for UI workflow automation where appropriate (e.g., validating critical user journeys, smoke checks during performance runs, test setup/teardown). - Integrate performance and automation testing into CI/CD pipelines (e.g., Jenkins, GitHub Actions, GitLab CI, Azure DevOps). - Maintain reusable test frameworks, utilities, and shared libraries for performance testing. - Instrument and monitor system behavior during tests using observability stacks such as Grafana (e.g., dashboards for latency percentiles, throughput, CPU/memory, saturation, error rates). - Correlate performance test results with application and infrastructure metrics to diagnose bottlenecks (app, database, network, third-party dependencies). - Produce performance test reports, trend analysis, capacity insights, and actionable remediation guidance. - Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness. - Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation. Required qualifications, capabilities, and skills - Formal training or certification on software engineering concepts and 3+ years applied experience - Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security. - Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices. - Practical experience with Apache JMeter for scripting and executing performance tests. - Experience using BlazeMeter for running/managing JMeter tests (distributed execution, results analysis, reporting). - Experience with Grafana for visualization and monitoring of performance test runs - Experience in Playwright and UI automation concepts - Strong understanding of performance engineering concepts: response time, throughput, concurrency, latency percentiles, SLAs/SLOs, and performance test design. - Proficiency in one or more languages such as JavaScript/TypeScript, Java, Python, or C#. - Experience with metrics/logging/tracing ecosystems (e.g., Prometheus, Splunk, ELK, Dynatrace, AppDynamics). - Experience with containerized/cloud environments (Docker, Kubernetes, cloud platforms) and database performance fundamentals (query analysis, indexing concepts). Preferred qualifications, capabilities, and skills - Familiarity with modern front-end technologies - Exposure to UI automation concepts - TypeScript/JavaScript preferred - Exposure to cloud technologies