Responsibilities
- Lead a High-Performing Team – Build, mentor, and guide a team focused on automated testing workflows and scalable validation infrastructure.
- Develop Scalable Testing Workflows – Deliver cloud-based automation that enables efficient feature validation, supports debugging of real-world issues, and scales requirement verification.
- Design Robust Automation Pipelines – Own the development of test orchestration, result aggregation, ETL pipelines, and traceability systems to streamline the validation lifecycle.
- Optimize Validation at Scale – Apply data-driven strategies to optimize cloud resource utilization, eliminate redundant testing, and ensure efficient validation cycles.
- Enable Data-Driven Insights – Incorporate data engineering capabilities to process and analyze large-scale test results, offering actionable feedback to engineering teams.
- Collaborate Across Key Functions – Partner with Simulation, Release Engineering, and Systems Engineering to ensure that testing workflows align seamlessly with development and validation milestones.
Minimum Qualifications
- 7+ years of software engineering experience, with 2+ years in engineering leadership roles.
- Strong background in cloud-based testing workflows, CI/CD integrations (e.g., Jenkins, GitLab, Kubernetes), and backend automation systems.
- Proven experience with large-scale cloud infrastructure for distributed testing and simulation (AWS, GCP, Azure).
- Proficiency in Python and C++, with expertise in automation pipelines and data processing workflows.
- Demonstrated ability to lead cross-functional teams and align engineering initiatives with business and product goals.
Nice to Haves
- Knowledge of data engineering and data science techniques to derive insights from large-scale test data.
- Experience working with functional safety standards (e.g., ISO 26262) for automotive software.
- Familiarity with ECU software deployment and related validation workflows.
- Background in integrating machine learning tools into customer workflows.
- Understanding of risk-based testing, regression analysis, and continuous validation methodologies.
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