Software Development Engineer - Test II, Alexa Endpoint Experiences
Amazon
Amazon
Join our dynamic team as an innovative Software Development Engineer in Test (SDET) specializing in Alexa Endpoint Experiences. This role is pivotal in modernizing our testing infrastructure by integrating AI tools and advanced automation frameworks. You will be instrumental in migrating manual test cases to fully automated solutions and constructing robust, multi-stage pipelines to guarantee comprehensive quality coverage for our cutting-edge products.
The Alexa Echo Show Composable Experience Platform team is responsible for the device and cloud-side stacks that drive the visual runtime experience on Echo Show devices. We deliver rich, seamless visual experiences on the Home screen and conversational interfaces to millions of users globally.
Your core responsibilities will include designing and implementing AI-powered frameworks to automate manual test cases and accelerate test generation. You will architect and develop fully automated CI/CD pipelines for efficient test execution, integrating static analysis tools for early defect detection and building scalable testing infrastructure that supports parallel execution. Furthermore, you will develop comprehensive functional, UI consistency, performance, and visual regression test suites to ensure the highest quality standards across various device form factors.
We are looking for candidates with at least 1 year of experience in building test automation frameworks and tools, and over 2 years of professional software development testing experience. Proficiency in at least one modern object-oriented programming language such as Java, C++, or C# is essential. Familiarity with penetration testing, exploitability-focused vulnerability assessment, and platform-level security mitigations for Linux and Windows is also required. Preferred qualifications include knowledge of system architecture, AI/ML tools for test automation, performance profiling, UI automation, and AWS services.
Amazon
Technology