rivianvw.tech Diagnostic System Test and Integration Engineer responsible for testing and integration of diagnostic software across vehicle sub-systems. Own testing from simulation to vehicle level ensuring robust diagnostics pre and post merge.
Responsibilities
Define and document test cases traced to requirements across OBD and enhanced diagnostics, from sub-system to vehicle level (white box to black box).
Develop and maintain automated SiL and HiL test cases in Python and Pytest for feature development and regression testing.
Run tests at the SiL, HiL and vehicle level through development, software release regression and production verification, and take part in MR reviews.
Plan and execute vehicle-level tests of the onboard and enhanced diagnostic systems, including test drives, data logging and analysis.
Design and perform physical fault injection on benches and vehicles (open and short circuits, connector disconnects, sensor and actuator faults) to validate fault detection, DTC setting and system reactions.
Find, reproduce and root-cause diagnostic issues with development engineers and software developers, and verify fixes.
Identify and build ways to automate and streamline testing across SiL, HiL and vehicle environments.
Qualification
Proficiency in PythonGenuine curiosity for how things workPrior EV experienceExperience with HiL benches
Required
BS or MSc in Engineering (preferably Electrical, Mechanical, Mechatronics or Software).
Proficiency in Python, including test automation with Pytest; familiarity with C and Git.
Ability to work hands-on with electromechanical (vehicle) systems and lab equipment (multimeters, oscilloscopes, breakout boxes).
Ability to troubleshoot and root-cause issues in complex systems.
Genuine curiosity for how things work, enthusiasm for test automation, and the drive to take system or software components apart to understand them.
Ability to prioritize and make decisions using a first-principles approach.
Ability to work with cross-functional teams, including external stakeholders, and communicate clear results.
Comfortable with AI-driven work and its pace.
Preferred
Prior EV experience.
Technical understanding of electric vehicle architecture.
Familiarity with Vector tools and vehicle communication protocols (CAN, ETH, LIN, DoCAN, DoIP, XCP).
Experience with HiL benches, vehicle testing or fault injection.
Exposure to requirements management tools (e.g. Flow).