Senior Firmware & System Debug Engineer

Microsoft•Redmond, WA
•$119,800 - $261,000

About The Position

Microsoft Silicon and Cloud Hardware Infrastructure Engineering (SCHIE) builds the infrastructure and foundational technologies that power Microsoft’s cloud services. The Firmware Center of Excellence develops firmware for Microsoft Cloud servers and racks, supporting hardware, silicon, and rack infrastructure from innovation through global operation. Microsoft’s first-party Firmware team is seeking a Senior Firmware & System Debug Engineer for future MAIA and Cobalt products. The role spans silicon bring-up through production fleet operation. You will lead embedded firmware development and investigations across firmware, silicon, hardware, operating systems, and drivers; build debug and telemetry-analysis capabilities; and use automation, data science, and AI-assisted tools to accelerate root-cause analysis at scale.

Requirements

  • Doctorate in Electrical Engineering, Computer Engineering, Computer Science, or a related field and at least 1 year of technical engineering experience; or a master's degree in one of these fields and at least 4 years of technical engineering experience; or a bachelor's degree in one of these fields and at least 5 years of technical engineering 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.
  • Eligibility to access export-controlled information; the successful candidate must provide proof of citizenship, U.S. residency, or other protected status, with citizenship verified using a valid passport. Applicable alternative documentation may be used by lawful permanent residents, refugees, and asylees.
  • Demonstrated experience in firmware development, debugging, technical investigations, and identifying fixes.

Nice To Haves

  • BS or MS in Computer Science or Engineering, or equivalent industry experience.
  • 8+ years of professional experience in embedded-system design, development, integration, validation, or system-level debugging.
  • Experience with cross-layer root-cause analysis of firmware, silicon, or system failures using logs, crash dumps, or telemetry.
  • Experience reading and debugging C/C++ firmware, together with scripting for automation or engineering-data analysis.
  • Experience with system-level debugging and validation of complex embedded systems, including boards, FPGA, emulation, or simulation environments.
  • Experience managing production or fleet issues through mitigation, root cause, corrective action, and post-deployment verification.
  • Experience with PCIe, memory subsystems, I2C, SPI, or other low-level platform interfaces.
  • Experience with silicon bring-up, firmware initialization, and lab or source-level debug tools such as JTAG, GDB, oscilloscopes, or logic analyzers.
  • Experience building automated diagnostic, test, or CI/CD pipelines and regression coverage.
  • Experience using Python, KQL/SQL or equivalent tools, and statistical methods for telemetry analysis, failure-signature grouping, or cohort comparisons.
  • Experience evaluating or applying AI-assisted tools to log or crash analysis, anomaly detection, or evidence-backed triage.
  • Experience mentoring engineers, documenting troubleshooting methods, and collaborating across firmware, silicon, hardware, OS, and fleet teams.

Responsibilities

  • Lead embedded firmware development, debugging, and fixes for silicon and system-on-chip issues.
  • Own complex investigations into firmware crashes, boot or reset failures, hangs, memory corruption, and hardware/software interaction issues across MAIA and Cobalt.
  • Correlate firmware logs, silicon error records, crash dumps, OS and driver traces, configuration, and fleet telemetry to isolate failure mechanisms.
  • Develop reproducible experiments and targeted diagnostic firmware or tooling to test hypotheses and distinguish firmware defects from silicon, hardware, or software causes.
  • Build scalable analysis and triage automation, including failure bucketing, signature detection, cohort comparisons, and regression detection.
  • Apply statistical analysis and AI-assisted methods to prioritize investigations and reduce manual analysis, validating results against independent evidence.
  • Drive mitigations and permanent fixes with component owners, and verify effectiveness through regression testing and post-deployment telemetry.
  • Translate investigation findings into improved instrumentation, test coverage, troubleshooting guidance, and mentoring.
© 2026 Teal Labs, Inc
Privacy PolicyTerms of Service