Senior Software Engineer, Hardware Management and AI-Driven Fleet Reliability

Minimum qualifications:

• Bachelor's degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages (e.g., Go, Python, C/C++, Java, Rust, etc), and with data structures and algorithms.
• 3 years of experience designing and building distributed infrastructure software, bare-metal server lifecycle automation, hardware management integrations (e.g., Redfish, BMC/iDRAC, Intelligent Platform Management Interface (IPMI), UEFI/BIOS, firmware management), or large-scale fleet monitoring and alerting systems.
• Experience with Linux systems programming, networking concepts, and container orchestration.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, a technical related field, or equivalent practical experience.
• Experience integrating multi-generation bare-metal server fleets (e.g., Dell PowerEdge, Google Compute Engine (GCE) Bare Metal, SmartNICs/DPUs, rack Power Distribution Units (PDUs)) with large-scale cloud or first-party fleet management, provisioning, and repair platforms.
• Experience architecting high-scale telemetry, monitoring, and alerting pipelines (e.g., Prometheus/OpenTelemetry exporters, time-series databases, SLO-motivated alerting, automated triage) for physical infrastructure and virtualization stacks.
• Experience designing state-machine or workflow-orchestrated machine management pipelines.
• Experience with enterprise virtualization stacks (e.g., VMware vSphere/ESXi, vSAN, NSX, VCF).

About the job

Responsibilities

• Own end-to-end, state-motivated workflows for bare-metal server provisioning, independent hardware/firmware bundle rollouts and secure physical hardware decommissioning.
• Build end-to-end hardware and infrastructure observability pipelines and design high-signal, low-noise alerting and Service Level Objective (SLO) dashboards that drive sub-30-minute incident detection.
• Design and build seamless software integrations and abstraction layers between Google Cloud VMware Engine (GCVE) bare-metal infrastructure and Google's first-party hardware lifecycle, provisioning, repair, fleet management platforms.
• Design and implement high-reliability recovery orchestration including one-click staggered rack/row power-up, automated thermal protection shutdowns, and deterministic host/cluster restoration.
• Apply Artificial Intelligence/Machine Learning (AI/ML) models, time-series anomaly detection, and agentic Root Cause Analysis (RCA) workflows over hardware telemetry, system logs, and crash dumps to predict imminent hardware failures.