Senior QA Automation Engineer
About the role
About Juniper Square
Juniper Square's mission is to unlock the full potential of private markets. Privately owned assets like commercial real estate, private equity, and venture capital make up half of our financial ecosystem yet remain inaccessible to most people. The company is digitizing these markets, bringing efficiency, transparency, and access to one of the most productive corners of our financial ecosystem.
Juniper Square operates with a digital-first approach, allowing teams to collaborate effectively across 27 U.S. states, 2 Canadian Provinces, India, Luxembourg, and England.
About Your Role
As a QA Engineer at Juniper Square, you will collaborate with product and engineering teams to help define and drive manual and automation testing efforts. You must be detail oriented, passionate about product quality, and a strong advocate for the end user experience.
What You'll Do
- Review functional specifications and technical design documents, providing meaningful feedback and using AI-assisted analysis to identify edge cases or logic gaps early in the SDLC
- Work closely with development teams to identify test cases for automation and leverage AI-powered IDEs to rapidly prototype and scaffold new test suites
- Design, develop, and execute test cases against product features and backend systems
- Maintain and extend automation frameworks (Playwright/Locust) by utilizing LLMs for code refactoring, optimizing test scripts, and reducing flaky test patterns
- Contribute to your development team on best practices, processes, and problem-solving, including the ethical and effective use of AI tools in the QA workflow
- Develop automated test result reports and highlight any potential quality risks
- Identify, troubleshoot, and track bugs to resolution, using AI tools to assist in root cause analysis and log interpretation
- Be an advocate for automation: Partner with the engineering team to provide recommendations on how to decrease manual efforts through automated solutions and AI-driven test generation
- Design evaluation frameworks for LLM-powered features, including prompt regression testing and behavioral drift detection
- Proactively leverage AI tools to accelerate test authoring, debugging, and maintenance of automation frameworks
- Use AI to diagnose failures, generate test scenarios, and improve coverage and efficiency