Principal Hardware Engineer

• Lead development and implementation of end-to-end agentic/automated debug solutions for @scale datacenter fleet health systems.
• Lead collaboration projects with hardware, firmware and software teams that drive root cause analysis for one flow end to end; sets the rules agents work within; clears handoffs and share of work closed by agents
• Accountable for successful execution of targeted agentic defect reduction workflows for novel faults that cross SW, blade components, rack and fleet; turns every fix into a reusable lesson.
• Lead resolution of complex problems based on technical and business understanding. Sets the goals, specs and evidence bars agents build from to minimize errors caught late.
• Develop world class at scale debug methodologies to solve problems relating to mission critical services and build automation to drive debug efficiency.
• Accountable for fleet health agent quality and reliability. Runs persona swarms safely; sets runtime limits for agentic support on incident response and recovery time for agent faults.

Computer Engineering, Xbox, Microsoft Windows Azure, Microsoft Bing Search Engine, Microsoft Product Family, Customer Experience, Cloud Computing, Network Operations Center, Computer Engineering, Sustainability, Masters Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 7+ years technical engineering experience OR Bachelors Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 8+ years technical engineering experience OR equivalent experience.

Other: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter., * 10+ years of technical leadership and a record of owning a measured reliability, quality, capacity or recovery outcome at production scale, using reliability engineering methods (failure-mode analysis, failure-rate statistics, screening and qualification) and working across hardware, firmware and software teams.

• Deep expertise in at least one layer of server or datacenter infrastructure (CPU or SoC architecture, memory subsystem, storage, networking, virtualization, firmware, cloud-native operating systems, or fleet telemetry and data systems), with working fluency in how failures propagate.
• Proven ability to lead deep dives into hard failures that have no known playbook, in at-scale environments: testing competing hypotheses, preserving evidence before repair, finding root cause across layers, and converting the result into a permanent fix, runbook, test or automated check
• A record of setting intent and limits for automated or AI-driven systems: defining success criteria and the evidence bar, evaluating results against outcomes, and deciding what may act without prior human approval, with rollback, an audit trail and a named accountable owner.
• Experience with AI agents in production operations: setting intent and success criteria, evaluating output against outcomes, curating the memory they rely on, governing what each may do, and solving the problems they have not seen.
• Analytical rigor with large-scale telemetry and data tools: defining each metric once (population, start and end events, denominator), separating measured results from targets, proxies and estimates, and counting distinct machines, not retries.
• Experience leading without line authority across organizational boundaries: aligning partners on workflow ownership, interfaces and decision rights, and adopting ideas from other teams on evidence.
• Decision-ready communication for engineers and executives in writing, visuals and live forums, including technical reports that state the conclusion, the evidence, the confidence and what would change the answer.
• Planning discipline in a fast-changing environment: works in small, reversible steps, adapts as evidence changes, manages time and priorities, and sets a pace of change the team can absorb.

Hardware Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.

Microsoft Silicon, Cloud Hardware, and Infrastructure Engineering (SCHIE) is the team behind Microsoft’s expanding Cloud Infrastructure and responsible for powering Microsoft’s “Intelligent Cloud” mission. SCHIE delivers the core infrastructure and foundational technologies for Microsofts over 200 online businesses including Bing, MSN, Office 365, Xbox Live, Teams, OneDrive, and the Microsoft Azure platform globally with our server and data center infrastructure, security and compliance, operations, globalization, and manageability solutions. Our focus is on smart growth, high efficiency, and delivering a trusted experience to customers and partners worldwide and we are looking for experienced engineers to achieve that mission.

As Microsofts cloud business continues to grow the ability to deploy new offerings and hardware infrastructure on time, in high volume with high quality and lowest cost is of paramount importance. To achieve this goal, the Hardware, Infrastructure Management, and Fundamentals Engineering (HIFE) team is instrumental in defining and delivering operational measures of success for hardware manufacturing, improving the planning process, quality, delivery, scale and sustainability related to Microsoft cloud hardware. We are looking for engineers with a dedicated passion for customer focused solutions, insight and industry knowledge to envision and implement future technical solutions that will manage and optimize the Cloud infrastructure.