Software Engineer II

Design, implement, test, document, and operate scoped features of the CER Lab's packaged Windows validation product. Build and evolve harness components, runners, scheduling, device orchestration, environment management, and result processing. Investigate test failures using logs, traces, crash data, Windows debugging tools, and structured experiments; drive assigned issues to root cause and mitigation. Produce clear component designs, write secure and maintainable code, participate in design and code reviews, and improve engineering practices through feedback. Add telemetry, logging, tracing, health checks, and error handling so automation is observable, supportable, and actionable. Improve test reliability and operational maturity by addressing flaky execution, environmental variance, performance bottlenecks, and recurring failure patterns. Apply approved AI-assisted engineering tools to test authoring, failure classification, log analysis, bug filing, development, and documentation while validating results. Collaborate with software engineers, data engineers, data scientists, lab operators, program managers, Windows teams, and OEM partners on requirements and integration. Support less-experienced engineers through code review, technical guidance, shared debugging, and examples of solid ownership. Contribute estimates, risks, technical options, and measurable outcomes to planning for assigned workstreams. Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python. OR equivalent experience. Experience owning and operating production-quality test automation, developer tooling, lab infrastructure, distributed services, or continuous integration capabilities. Experience with Windows debugging, operating system fundamentals, system internals, drivers, deployment, power, performance, reliability, or hardware/software integration. Experience designing harnesses, runners, device or lab orchestration, telemetry, logging, tracing, and result aggregation. Experience diagnosing complex failures, reducing flaky tests, improving observability, and driving issues through mitigation and verification.