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

info_outline XIn most instances, this position requires in-person interviews as part of the hiring process 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 jobGoogle Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems. 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.