Job Summary

Platform Test Engineer (3 - 7 Years) Work in a multi-cultural engineering environment with teams across Europe and India.

Contribute to the validation of cutting-edge features driving modern Automotive technology megatrends such as Software Defined Vehicles (SDV), High-Performance ECUs, Zonal Architectures, and Car-to-Cloud connectivity.

You will be responsible for deriving functional and non-functional test specifications, developing automated test suites, and validating system behavior in End-to-End use cases involving multiple components along the functional chain. The role increasingly leverages AI-powered tools and workflows to enhance test efficiency, traceability, and coverage.

Responsibilities

Platform Test Engineer (3 - 7 Years)

- Derive and document functional and non-functional test specifications.
- Automate test scenarios using Python, Robot Framework, and AI-assisted coding tools.
- Perform End-to-End system validation across multiple ECUs and software subsystems.
- Analyze system traces, logs, and communication traffic to detect and diagnose issues.
- Incorporate AI-driven testing methodologies to optimize test generation, trace analysis, and anomaly detection.
- Ability to craft effective AI prompts for generating test scripts, documentation, and analysis reports.
- Use prompt-engineering techniques to interact with AI models for generating test artifacts, summaries, and reports.

Required Skills

Automotive Platform-Testing

- Experience in the Automotive domain, especially in SDV / SW ECU Platforms




- Positive understanding of automotive ECUs and features (Communication protocols, BSW, MCAL, Diag stack etc.)
- Strong expertise in Test Automation with Python and Robot Framework.
- Experience with Linux/Android/QNX systems, including file systems and network configuration.
- Knowledge of automotive communication protocols: CAN, FlexRay, Ethernet, SOME-IP and DOIP
- Able to generate Rest Bus Simulations from Network data / ARXML .
- Understanding of End-to-End Protection (E2E) profiles
- Experience with trace/log analysis (DLT, CAN, Ethernet) and tools like Vector CANoe, VehicleSpy, Wireshark.
- Experience in automotive diagnostics: OBD, UDS, DoIP; familiarity with tools such as CANoe, DiVa and CANape.
- Experience in network node simulation using CAPL (CANoe) or function blocks (VehicleSpy).
- Knowledge of automotive test processes and tools for Requirements Management (DOORS, CodeBeamer), Planning (ALM/Jira), and Version Control (Git/SVN).
- Experience in AI-driven testing methodologies to optimize test generation, trace analysis, and anomaly detection.

Good to Have (Optional)

- ISTQB Certification.
- Adaptive AUTOSAR experience.
- Experience in containerized environments (Docker, Conan).
- Workflow/CI creation in GitHub for continuous test automation.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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