Senior Software Development Engineer in Test

In this role, you will:

• Lead the design, development  and maintenance of large-scale event-driven software/hardware -in-the-loop (SIL/HIL) tests and testing frameworks, utilizing advanced software patterns to improve modularity and reduce code duplication.

• 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.

• Provide technical leadership and mentorship to a small group of engineers on the team.

Qualifications:

• 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.

Bonus Qualifications:

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).