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Tier-1 employer and metro location, but highly specialized automotive validation reduces applicant pool.
Highly domain-specific ADAS, ASPICE, ISO26262, and simulation expertise makes cross-industry transferability low.
Explicit 8–12 years plus mandatory automotive validation, bisection, Python, and safety/process requirements create high filtering.
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Lead daily pre-merge testing and manage automotive simulation failure triage to ensure timely resolution of critical issues.
Perform root-cause and multi-source failure analysis to isolate software, simulation, or infrastructure errors and identify regression-causing changelists through systematic bisection.
Develop Python automation tools and apply Agentic AI workflows to accelerate failure investigation, evidence correlation, classification, and reporting while coordinating cross-functional teams.
Bachelor's degree in CS, CE, ECE, EEE, Automotive Engineering, or related field.
8–12 years of experience in automotive software testing, simulation validation, and root-cause analysis using signals, logs, and traces.
Advanced Python programming skills for automation and tooling development; proven experience with Git-based bisection and CI/CD pipelines.
Work Experience Required: 8-12 years in automotive software validation and testing; notice period: Not explicitly mentioned in the JD.
Experienced leader capable of managing small to mid-sized teams and driving cross-team coordination in a fast-paced automotive testing environment.
Strong domain expertise in ADAS and automated-driving feature validation across perception to control layers, with hands-on HIL/SIL simulation testing experience.
Proficient in applying AI/Agentic workflows and automation to enhance failure triage efficiency and continuous quality improvements.