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Job Details
Posted date: Jun 25, 2026
Location: Kirkland, WA
Level: Executive
Description
Drive the strategic direction, engineering execution, and commercialization of the general-purpose compute portfolio across both x86 and ARM architectures. Lead the design and delivery of foundational node-level platform capabilities, including overcommit technologies (vCPU/memory overcommit), on-host system live updates, and performance regression management. Advocate for next-generation hypervisor and microVM development to build secure, high-density substrates for agentic AI workloads and sandboxed environments. Collaborate with cross-functional leadership across technical infrastructure teams (cluster management, container platforms, hardware platform engineering, and security) to align on roadmaps, resource planning, and shared infrastructure goals. Manage senior technical talent, engineering managers, and the performance engineering team, while resolving critical customer escalations and ensuring operational excellence across the global compute fleet.Google’s AI and Infrastructure (AI2) organization’s mission is to "empower customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity." We build the foundation behind Google and Google Cloud’s compute and AI/ML offerings. We manage the underlying design elements, developer platforms, product components, and infrastructure.
As the Director, Engineering, General Purpose and Node Platform, you will serve as the single-threaded executive leader responsible for Google Cloud's foundational general-purpose compute portfolio (spanning general-purpose virtual machine instance families on both x86 and ARM architectures) and node-level technologies. Your primary mission is to drive the strategic development, operational execution, and performance optimization of Google Compute Engine's (GCE) core node platform, delivering hyper-scale efficiency, extreme overcommit technology, and disruption-free live update capabilities. You will also oversee the GCE Performance team to systematically manage performance regression and variance at scale.
As AI and agentic workloads redefine computing, you will lead the critical charge to deliver high-performance, secure, and dense microVM/sandbox substrates on bare metal and nested configurations. In this highly cross-functional role, you will collaborate deeply with technical infrastructure partners (cluster management, Kubernetes, hardware platforms, security) to align on roadmaps, manage resource allocation, and ensure fleet compliance. You will directly engage with major foundation model companies and enterprise partners to translate their compute demands into next-generation platform features. This is a premier leadership opportunity to shape the core infrastructure driving Google and the industry’s AI revolution.
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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $307000 - $428000 (USD) + 30% bonus target + equity + benefits
Learn more about benefits at Google.
Qualifications
Minimum qualifications: Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience. 15 years of professional experience in software engineering, including team leadership and people management. Experience with cloud infrastructure systems, virtualization substrates, or low-level systems engineering.Preferred qualifications: Master’s degree or PhD in Computer Science, Engineering, or a related technical field. Experience driving large-scale, multi-year cross-functional programs (e.g., cluster management, Kubernetes, or container engine integrations) under tight deadlines. Experience managing and scaling engineering teams responsible for core cloud infrastructure products. Deep technical knowledge of hypervisors (Hyper-V, KVM, Zen, Cloud Hypervisor), virtual machine managers (VMMs), or Linux kernel internals. Ability to navigate ambiguity, manage high-stakes customer escalations, and align stakeholders around strategic infrastructure decisions. Excellent communication and collaboration skills, with a track record of translating complex technical trade-offs for both executive leadership and enterprise partners.