Job description

As a Hardware Specialist, you will lead the technical delivery of confidential compute projects for customers. You will serve as the primary technical liaison between global clients, internal engineering teams, and internal operations. Your role involves maintaining on-prem and cloud-based environments, ensuring seamless integration of high-performance accelerators with enterprise-grade networking and storage to support the next-generation of mission-critical, data-intensive workloads. 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: $152000 - $221000 (USD) + 15% bonus target Learn more about benefits at Google . • Oversee the end-to-end deployment of accelerated compute clusters, serving as the lead technical advisor for confidential, enterprise infrastructure initiatives. • Collaborate with customer technical leads and client executives to manage and deliver successful implementations of technical solutions for high-density computing environments. • Partner with internal specialists, Product, and Engineering teams to package technical playbooks, best practices, and reference architectures for high-performance computing, influencing the roadmap for next-generation hardware and software integration. • Engage with sales and partners to manage project scope, priorities, deliverables, risks and issues, and timelines for successful client outcomes. • Travel approximately 30% of the time for client engagements. • Bachelor's degree in Computer Science, Electrical Engineering, a related technical field, or equivalent practical experience. • 5 years of experience in technical solution delivery and project management for enterprise infrastructure projects. • 4 years of experience in technical architecture, systems administration, or infrastructure delivery in cloud or on-prem environments. • Experience managing customer relationships and project stakeholders, including executive-level communication and influence on technical and operational decisions. • Experience in hardware triage, diagnostics, and guiding repair workflows for server clusters and high-performance networks. Minimum qualifications: • Bachelor's degree in Computer Science, Electrical Engineering, a related technical field, or equivalent practical experience. • 5 years of experience in technical solution delivery and project management for enterprise infrastructure projects. • 4 years of experience in technical architecture, systems administration, or infrastructure delivery in cloud or on-prem environments. • Experience managing customer relationships and project stakeholders, including executive-level communication and influence on technical and operational decisions. • Experience in hardware triage, diagnostics, and guiding repair workflows for server clusters and high-performance networks. Preferred qualifications: • Master's degree or PhD in Computer Science or Engineering, or a related field. • Experience with end-to-end system architecture or accelerated computing hardware (e.g., Kubernetes, GKE, EKS, GPU workloads, or Linux-based distributed systems). • Experience with networking and system design of load balancers, firewalls, and VPN in architecting, developing and maintaining production-grade systems. • Experience in maintaining clusters of massive-scale model training using high-end hardware accelerators and AI/ML infrastructure frameworks such as JAX, PyTorch, or OpenXLA.

Requirements

Must-haves

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Learn more about benefits at Google .
Oversee the end-to-end deployment of accelerated compute clusters, serving as the lead technical advisor for confidential, enterprise infrastructure initiatives.
Collaborate with customer technical leads and client executives to manage and deliver successful implementations of technical solutions for high-density computing environments.
Engage with sales and partners to manage project scope, priorities, deliverables, risks and issues, and timelines for successful client outcomes.
Travel approximately 30% of the time for client engagements.
Bachelor's degree in Computer Science, Electrical Engineering, a related technical field, or equivalent practical experience.
5 years of experience in technical solution delivery and project management for enterprise infrastructure projects.
4 years of experience in technical architecture, systems administration, or infrastructure delivery in cloud or on-prem environments.
Experience managing customer relationships and project stakeholders, including executive-level communication and influence on technical and operational decisions.
Experience in hardware triage, diagnostics, and guiding repair workflows for server clusters and high-performance networks.
Bachelor's degree in Computer Science, Electrical Engineering, a related technical field, or equivalent practical experience.
5 years of experience in technical solution delivery and project management for enterprise infrastructure projects.
4 years of experience in technical architecture, systems administration, or infrastructure delivery in cloud or on-prem environments.
Experience managing customer relationships and project stakeholders, including executive-level communication and influence on technical and operational decisions.
Experience in hardware triage, diagnostics, and guiding repair workflows for server clusters and high-performance networks.

Nice-to-haves

US: $152000 - $221000 (USD) + 15% bonus target
Master's degree or PhD in Computer Science or Engineering, or a related field.
Experience with end-to-end system architecture or accelerated computing hardware (e.g., Kubernetes, GKE, EKS, GPU workloads, or Linux-based distributed systems).
Experience with networking and system design of load balancers, firewalls, and VPN in architecting, developing and maintaining production-grade systems.
Experience in maintaining clusters of massive-scale model training using high-end hardware accelerators and AI/ML infrastructure frameworks such as JAX, PyTorch, or OpenXLA.

Application prep

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Keywords to mirror

kubernetesaiml

Platform: google
Effort: medium