Senior Hardware Engineer

Job d:

Location:

United States, California, Mountain View Salary: USD $119,800 - $234,700 per year

Employment type:

Full-Time Work site: 3 days / week in-office

Role type:
Individual Contributor Travel:
Less than 25%
Profession:
Hardware Engineering Discipline:
Hardware Engineering Company:
Microsoft Overview As  Microsoft’s cloud continues to scale, our ability to deploy new hardware platforms and infrastructure quickly, reliably, and cost effectively is critical. The Hardware, Infrastructure Management, and Fundamentals Engineering (HIFE) organization drives hardware readiness, quality, reliability, and operational excellence across Microsoft’s cloud infrastructure.

Fleet Engineering is transforming how complex infrastructure problems are solved by combining systems expertise with telemetry, automation, AI, and agentic workflows. We are looking for a Sr. Hardware Engineer to solve challenging hardware, firmware, software, and system-level problems across Microsoft’s Global Azure Cloud enabled by remote, at-scale engineering capabilities. The role turns deep engineering insights into scalable diagnostics, automation, intelligent workflows, and reusable capabilities that improve Fleet readiness, reliability, diagnosability, and recoverability.#azurehwjobs

#HIFE #SCHIEResponsibilities

Architect and deliver AI-native, end-to-end system debug solutions for hyperscale datacenter infrastructure, combining engineering expertise, telemetry, automation, and agentic workflows.

Design and orchestrate human-agent engineering workflows that accelerate failure detection, triage, segmentation, root cause analysis, mitigation, remediation, and learning.

Build specialized engineering agentic skills, tools, and reusable workflows that codify expert debug knowledge and enable autonomous or human-supervised execution d cross-functional debug and root-cause initiatives spanning hardware, firmware, software, platform, and datacenter systems, using agents and automation to reduce coordination and investigation overhead.

Own measurable improvements in system reliability and debug effectiveness, including faster fault isolation, reduced time to root cause, defect reduction, automation coverage, and prevention of repeat failures.

Lead investigation of complex and ambiguous system failures, applying deep technical judgment where automated or agentic systems encounter novel scenarios, insufficient evidence, or conflicting signals.

Develop world-class at-scale debug methodologies, diagnostic strategies, validation techniques, and automated test routines for datacenter systems.

Engineer closed-loop learning systems that convert incidents, debug evidence, root causes, and engineering decisions into reusable knowledge that continuously improves agents, automation, diagnostics, and future platform readiness.

Define safe and governed agentic execution models, including human-in-the-loop controls, validation, observability, permissions, and escalation paths for mission-critical engineering workflows.

Drive the transition from engineer-driven execution to outcome-driven engineering, where engineers define intent and guardrails while agents perform appropriate investigation, correlation, orchestration, and repetitive execution.

Provide technical leadership on emerging AI, agent, diagnostic, telemetry, and automation technologies, identifying opportunities to fundamentally improve how Fleet Engineering operates at datacenter scale.

Communicate complex engineering insights, decisions, risks, and progress through data-driven narratives that enable effective collaboration and decision-making across engineering teams, partners, and leadership.

Qualifications

Required Qualifications:

Master's Degree in Electrical Engineering, Computer…