Principal Firmware Debug & Dev Engineer
About The Position
Microsoft Silicon and Cloud Hardware Infrastructure Engineering (SCHIE) builds and operates foundational technologies for Microsoft’s global cloud infrastructure. The Firmware Center of Excellence develops firmware that powers servers and racks across the globe, supporting Microsoft cloud services and Azure. The team works on next-generation hardware and firmware for server, silicon, and rack infrastructure, with an emphasis on firmware innovation and securing Azure infrastructure. The Principal Firmware Debug & Dev Engineer drives product quality from bring-up through deployment. This role leads complex investigations across firmware, silicon, boards, operating systems, drivers, and fleet infrastructure; improves firmware architecture and implementation for diagnostics and reliability; and develops reusable methods for telemetry, failure analysis, and regression prevention. The engineer applies AI- and data-science-assisted debugging, helps establish diagnostic readiness before deployment, influences cross-team priorities, and mentors engineers while remaining hands-on with challenging technical work.
Requirements
- Doctorate in Electrical Engineering, Computer Engineering, Computer Science, or a related field and 3+ years of technical engineering experience; or a master's degree in one of these fields and 6+ years of experience; or a bachelor's degree in one of these fields and 8+ years of experience; or equivalent experience.
- Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.
- Must meet applicable export-control eligibility requirements and provide documentation to verify citizenship, U.S. residency, or other protected status; citizenship is verified with a valid passport, with other status documents accepted where applicable.
- Experience with system or silicon debug, firmware development in C or C++, and validation using scripting for engineering automation.
- Experience leading cross-functional silicon or system investigations and delivering firmware or debug solutions from power-on/bring-up into deployed products.
- Experience defining firmware/software diagnostics or observability and using telemetry or automated analysis to resolve complex system failures.
- Experience with SoC architecture, platform initialization, memory subsystems, PCIe or other low-level interfaces, and OS/RTOS concepts such as scheduling, interrupts, and concurrency.
- Experience with firmware security, error reporting, crash capture, recovery, and reliability mechanisms.
- Experience with silicon/platform bring-up, lab debugging, and deployment of reusable diagnostics or regression coverage.
- Experience applying Python, KQL/SQL or equivalent analysis tools, statistical methods, or AI-assisted diagnostics to fleet failure analysis, including evaluation of evidence quality and false positives.
- Experience influencing cross-product engineering priorities, mentoring technical leaders, and turning investigation findings into firmware or platform design improvements.
Nice To Haves
- 12+ years of technical engineering experience; or a bachelor's degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or a related field and 10+ years of technical engineering experience; or a master's degree in one of these fields and 7+ years of experience; or a doctorate in one of these fields and 5+ years of experience.
Responsibilities
- Drive product quality from bring-up to deployment in partnership with cross-organizational teams.
- Lead critical, ambiguous investigations spanning firmware, silicon, boards, operating systems, drivers, and fleet infrastructure; establish evidence-based root causes and corrective actions.
- Guide firmware architecture and implementation decisions to improve error reporting, crash capture, recovery, diagnosability, and reliability.
- Establish reusable approaches for telemetry quality, failure classification, fleet-scale correlation, reproducibility, and regression prevention.
- Lead AI- and data-science-assisted debugging methods, evaluating accuracy, false positives, engineering usefulness, and data-handling controls.
- Define diagnostic readiness and knowledge-transfer expectations with component teams before deployment and broader fleet adoption.
- Influence cross-team priorities and mentor engineers while remaining directly engaged in difficult technical problems.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Principal
