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Senior Quality Assurance Automation Engineer

stellus rx·Worldwide·Peru·senior
cypressselenium
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Job Summary We're opening eyes, hearts and minds to the impact that a pharmacy team can have in changing lives. Join our group of talented, committed team members-pharmacists, pharmacy care coordinators, technologists, product strategists and more-to create and expand the delivery of personalized health support that people didn't even know could be possible. The Senior QA Automation Engineer for Stellus Rx will be a key member of our Technology Team, working closely with Stellus Rx leaders and across the organization to unlock the health of millions of Americans. We are a culture that is unabashedly driven by purpose — making a difference to patients and team members while growing at an accelerated rate. This role is built for a QA engineer who uses AI as a core part of how they test — generating test cases intelligently, automating coverage analysis, and replacing manual quality activities with smarter, faster, AI-driven approaches across the full software delivery lifecycle. Role and Responsibilities: AI-Driven Test Design & Automation Use AI tools to generate, review, and optimize automated test cases — replacing manual test authoring wherever possible and dramatically expanding coverage without proportional increases in effort. Leverage AI-assisted analysis to understand code flow, component interactions, and edge cases, ensuring automation suites reflect real-world usage scenarios rather than just happy paths. Build and maintain automation test suites across Mobile, Desktop, and Web platforms using frameworks such as Selenium, Appium, Cypress, Robot Framework, or Tricentis Tosca — augmented by AI to accelerate framework setup and test scaffolding. Apply AI tools to identify gaps in existing test coverage, prioritize high-risk areas, and continuously improve the depth and reliability of automation suites. AI-Augmented Bug Detection & Reporting Use AI-powered analysis to investigate user problems, detect patterns in defect data, and surface systemic quality issue

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