Qa Software Engineer III

JPMorgan Chase JPMorgan Chase · Banking · Palo Alto, CA +1 · Commercial & Investment Bank

Software Engineer III in Test at JPMorgan Chase, focused on designing, developing, and maintaining automated test scripts and ensuring product quality. The role involves leveraging enterprise-authorized AI coding assist tools to improve code quality and delivery speed, while also understanding and applying responsible AI use in engineering workflows. This is a QA role within a financial services company, not a core AI/ML development role.

What you'd actually do

  1. Design, develop, and maintain automated test scripts using industry-standard tools and frameworks such as Selenium, TestNG, Cucumber, RestAssured, and Playwright.
  2. Perform comprehensive testing including functional, accessibility, integration, regression, performance, and API testing.
  3. 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.
  4. 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.
  5. Identify opportunities for test automation and actively contribute to the overall test strategy.

Skills

Required

  • Java
  • Selenium
  • TestNG
  • RestAssured
  • BDD frameworks
  • Cucumber
  • Playwright
  • UI testing
  • database testing
  • API testing
  • enterprise-authorized AI-assisted software development tools
  • responsible AI use
  • API testing tools
  • Postman
  • CI/CD tools
  • Jenkins
  • GitLab CI
  • software test automation
  • SDLC tools
  • Git/Bitbucket
  • Jira
  • Gradle
  • Maven

Nice to have

  • Experience integrating and utilizing AI tools for test automation and analysis.
  • component testing
  • contract testing
  • integration testing
  • acceptance testing
  • end-to-end testing
  • accessibility testing
  • performance testing
  • Spinnaker
  • GitHub
  • JMeter
  • BlazeMeter
  • PactFlow
  • developing in-sprint test automation scripts

What the JD emphasized

  • 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.