A contract position Inside IR35
Hybrid working - 3 days onsite.
Automotive ADAS experience essential. Hands-on ADAS Automation Test Engineer to build and scale test automation for advanced driver-assistance features.
You will primarily work with Vector CANoe/CAPL to automate tests, translate Gherkin/KTD/ATS test cases into CAPL scripts, and convert Python test logic to robust CAPL implementations. You'll collaborate closely with system, software, and validation teams to ensure high-quality, reliable releases for production programs.
Key Responsibilities
Test Automation Development
Design, implement, and maintain automated test scripts in CAPL within Vector CANoe for ADAS ECUs and functions (e.g., ACC, AEB, LKA, APA).
Translate Gherkin/KTD keyword-based and ATS manual test cases into executable CAPL automation.
Convert existing Python-based tests and utilities to CAPL (or orchestrate Python-CANoe integrations where appropriate).
Test Execution & Infrastructure
Configure CANoe environments (databases, panels, CAPL DLLs, simulation nodes) for CAN/LIN/FlexRay/Ethernet (SOME/IP).
Execute automated regression suites on HIL benches / SIL environments, analyse results, and triage failures.
Develop test stubs, signal generators, rest-bus simulations, and trace analysers for ADAS scenarios.
Protocols & Diagnostics
Implement and validate UDS/ISO 14229 diagnostics, DoIP, and Flash/ECU programming flows as part of automation.
Quality, CI/CD & Reporting
Integrate test suites with CI/CD (e.g., Jenkins/GitLab CI); enable nightly runs and dashboards.
Create clear test reports (KPIs, coverage, pass/fail, trends); manage defects via Jira/Azure DevOps.
Contribute to test strategy, traceability to requirements (e.g., DOORS/Polarion), and coverage closure.
Collaboration
Work with feature owners, system architects, and safety teams to define acceptance criteria, edge cases, and negative tests.
Mentor junior engineers on CAPL best practices, Vector tooling, and test automation patterns.
Required Qualifications
Experience in automotive software testing or validation, with significant Vector CANoe/CAPL experience is essential.
Strong background in ADAS systems and behaviour-driven or keyword-driven testing (Gherkin/KTD/ATS) with demonstrable conversion to CAPL.
Practical knowledge of CAN/LIN/FlexRay/Ethernet (SOME/IP), signal databases (DBC/ARXML), and network simulation.
Experience with Python for test logic/utilities and ability to port/translate Python tests to CAPL.
Hands-on with UDS diagnostics, DoIP, logging/tracing (BLF/ASC), and timing/latency measurements.
Familiarity with CI/CD tools (Jenkins, Git/GitLab), test management, and defect tracking (Jira/Azure DevOps).
Solid understanding of software QA principles: requirements traceability, coverage, negative/robustness testing