Architect and manage end-to-end continuous integration (CI) pipelines to automate the execution of regression suites.
Lead root cause analysis for complex system-level failures, developing log mining scripts and visualization dashboards (e.g., Grafana, SQL-based notebooks) to triage failures and track performance metrics.
Perform gap analyses between high-level safety requirements and technical test implementations, including the development of intricate timing and prioritization patterns. Lead end-to-end validation and clearance process for safety-critical monitors, such as for collision detection systems.
Bachelor's or higher degree in Mechatronics Engineering, Computer Science, Electrical Engineering or a relevant technical field.
7+ years of experience with demonstrated ownership of 3+ complex projects
Good technical communication skills, with the ability to summarize complex test failures and provide clear impact assessments for our tests, tools, and pipelines.
Demonstrated experience delivering complex projects in Python, including the use of AI-based coding, such as for infrastructure development, tooling and automated test writing.
Deep understanding of HIL and SIL methodologies, including real-time fault injection.
Ownership from design, to implementation and maintenance of automated testing pipelines (e.g., using Bamboo, Buildkite, Jenkins, or similar CI Tools) and developing custom automation plugins.
Practical knowledge of Linux internals and networking protocols used in high-throughput real-time systems.
Strong C++
Pytest customization experience
Background in autonomous systems or safety-critical robotics validation.
Experience applying Generative AI or Machine Learning tools to code, audit and improve test coverage and documentation.
Experience with real-time communication protocols (e.g., DDS, I2C, SPI, CAN, GMSL2).
Design and maintain automated tests for onboard embedded software, validating system behavior across hardware-in-the-loop platforms and helping teams detect, diagnose, and resolve issues before full-vehicle testing.
Design and deliver automated tests for onboard embedded software, validating system behavior across hardware platforms and HIL environments while improving test coverage, diagnostics, and developer self-service.
Lead the design and evolution of backend test frameworks and tooling for SaaS services, improving quality, reliability, and performance while integrating AI-driven workflows and mentoring engineers.
Lead the design and evolution of backend test frameworks and tools for SaaS services, shaping test strategy, integrating AI into QA workflows, and improving quality, reliability, and delivery.
Lead the design and evolution of backend SaaS test frameworks, tools, and strategies, integrating AI-enabled workflows to improve quality, reliability, coverage, and developer productivity.
