Design and develop crash dump collection, processing and analysis tools for GPU and AI accelerator platforms. Build hardware debugging tools for device inspection, failure analysis and low-level platform diagnostics. Develop diagnostic capabilities spanning host software, device drivers, firmware and accelerator hardware. Build tools for post-mortem debugging, failure triage and root-cause analysis. Develop scalable mechanisms for collecting and analysing logs, traces, telemetry and diagnostic data. Design extensible APIs and tooling that can support multiple hardware generations and accelerator architectures. Improve automation around failure detection, debugging and diagnostics to reduce engineering effort during complex system investigations. Work with hardware, firmware, driver, platform and cloud infrastructure teams to diagnose cross-layer issues. Drive improvements in tooling quality, reliability, testability, performance and developer experience. Participate in architecture and design reviews, contribute to engineering practices and mentor other engineers. Apply AI-assisted engineering practices across design, coding, testing, debugging and documentation to improve engineering velocity and software quality. Leverage AI-assisted workflows to accelerate crash analysis, code comprehension, failure triage, root-cause investigation and test development, while validating results through sound engineering practices. Identify opportunities to use AI to automate repetitive diagnostic and debugging workflows, reducing engineering effort and accelerating problem resolution. Use AI-assisted learning to develop deeper competency across systems software, computer architecture, firmware, drivers and AI accelerator infrastructure. Develop and share reusable AI-assisted engineering practices that improve team productivity, technical learning and domain competency. Bachelor's Degree in Computer Science, Computer Engineering, Electrical Engineering or related technical discipline, or equivalent experience with 8+ years of industry relevant experience. Software development skills in C, C++, C#, Rust, Python or similar languages. Experience developing systems software, debugging tools, diagnostic software or developer tools. Understanding of operating systems, computer architecture, memory management, concurrency and low-level software concepts. Debugging and problem-solving skills, including diagnosing complex software or hardware/software interaction issues. Experience developing reliable, maintainable and testable production software. Ability to use AI-assisted engineering tools and workflows to improve development, debugging, testing, technical learning and engineering effectiveness. Experience developing crash dump, debugger, tracing, profiling or diagnostic tools. Experience with GPU, AI accelerator or heterogeneous compute systems. Knowledge of PCIe, device interfaces, memory-mapped I/O or hardware/firmware interaction. Experience with Linux systems programming, kernel interfaces or device drivers. Familiarity with JTAG, OpenOCD or similar hardware debugging technologies. Experience with telemetry, tracing, logging, observability and post-mortem analysis. Understanding of firmware, embedded systems or SoC architectures. Experience building developer tools that operate across different hardware generations or platforms. Experience using AI-assisted techniques for code analysis, debugging, test generation, failure investigation or engineering automation. Ability to leverage AI-assisted learning to quickly develop expertise across new hardware architectures, firmware, drivers and diagnostic technologie AIINFRA This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. *

Microsoft