Seeking a seasoned Senior Test Developer to lead crucial automotive simulation testing and failure-triage initiatives. This role is for an experienced SWQA Lead with deep automotive domain knowledge and expertise in simulation testing. You'll be instrumental in integration testing quality and managing simulation failures, driving them to resolution.

Leverage your advanced Python skills to identify regression-causing code changes through systematic bisection. You will lead daily testing activities, analyze failures, pinpoint root causes, and coordinate efforts across multiple engineering teams. As the Person in Charge (PIC), you'll manage priorities, remove obstacles, and enhance triage efficiency, ensuring timely closure of release-impacting issues. Application of Agentic AI workflows to accelerate failure investigation and reporting is also a key aspect of this position.

Lead daily pre-merge testing and simulation failure triage, prioritizing tasks and ensuring timely closure of critical issues. Perform in-depth root-cause and signal-level analysis using logs, traces, and metrics to isolate various failure types. Conduct systematic bisections to identify culprit code changes and complex regressions. Develop Python-based automation tools for log analysis, failure classification, and reporting. Implement Agentic AI workflows to correlate diagnostic evidence and improve triage efficiency. Collaborate closely with development, simulation, validation, and infrastructure teams, tracking quality metrics and communicating risks.

Requires a B.Tech. degree in a relevant field (CS, CE, ECE, EEE, Automotive Engineering) with 8–12 years of experience in automotive software testing and validation. Must possess strong expertise in HIL/SIL, simulation testing, automotive verification workflows, and root-cause analysis. Hands-on validation experience with ADAS and automated-driving functions is essential. Advanced Python skills for automation, data analysis, and tool development are mandatory. Proven expertise in using Git and CI/CD pipelines for identifying and validating culprit code changes is required. Demonstrated ability to apply Agentic AI workflows and lead small to mid-sized teams is crucial. Excellent communication, documentation, and stakeholder management skills are necessary.