Quality Assurance Engineer II, Amazon RIVR

About the role

Amazon RIVR is a robotics company pioneering Physical AI through real-world doorstep delivery. Founded in 2024 as an ETH Zurich spin-off, RIVR developed wheeled-legged robots designed to operate in complex, unstructured environments such as stairs, gates, doors, and uneven urban terrain. We believe that achieving general physical intelligence requires solving real customer problems in the real world, where robots can learn from rich operational data at scale. Following our acquisition by Amazon in March 2026, we are continuing this mission with greater reach and speed. By combining custom robot hardware, onboard autonomy, and cloud-based coordination, Amazon RIVR is building the next generation of safe, reliable autonomous robots for last-mile delivery.

Requirements

• 4+ years of quality assurance engineering experience
• Experience in automation testing
• Experience as QA lead on medium to large sized projects
• Experience in UI and API automation testing (Selenium/SOAPUI)
• Experience troubleshooting and debugging technical systems, or experience that includes strong analytical skills, attention to detail, and effective communication abilities
• 4+ years of experience in QA Engineering, specifically within robotics, autonomous systems, or complex hardware-software integration.
• Demonstrated ability to write and maintain automated test scripts (Python preferred).
• Strong understanding of modern software development lifecycles and how they apply to physical robotic hardware.
• Experience with at least one automated test framework like Selenium or Appium
• Experience in gathering test requirements to create detailed test plans and defining quality metrics to measure product quality
• Experience with test plan development, building the necessary test bench infrastructure, developing tests and verifying the design
• Expertise across the full robotics stack (sensors, perception, localization, navigation, and control).
• Experience with automation tools and frameworks specifically designed for robotics (e.g., Isaac Gym, Gazebo, Foxglove, or custom HIL rigs).
• Background in last-mile delivery or autonomous vehicle regulatory compliance.
• Reinforcement learning experience
• Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Additional Information

We are seeking a highly technical QA Engineer to lead the end-to-end quality strategy for our robotic systems. In this role, you aren't just checking boxes; you are designing the full-system test architecture (covering both hardware and software) and automating the validation process. You will oversee the execution of these tests, working closely with Field Technicians and Test Support Engineers to ensure high-quality data collection and reporting. As the bridge between the field and product development, you will transform feedback from our Field Engineers into robust, automated test suites that ensure our robots meet the highest standards of safety and reliability. Key job responsibilities ● Design and architect comprehensive full-system test cases encompassing hardware-in-the-loop (HIL), software-in-the-loop (SIL), and functional safety. ● Automate test plans to drive efficiency and scalability across our global testing sites (Zurich, Austin, and beyond). ● Oversee the execution of test plans by Field Technicians and Test Support Engineers, providing the technical guidance they need to report results accurately. ● Synthesize technical input from Field Engineers and Product teams to align testing strategies with real-world failure modes and business goals. ● Reproducing complex bugs discovered in the field in a testing controlled setup, prioritizing them for the engineering team based on severity and operational impact. ● Document hardware and software test results and provide clear, actionable reports to the engineering team ● Continuously "raise the bar" for internal testing standards, ensuring the team levels up in technical knowledge and execution.

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