PitchMeAI
Google

Data Center Hardware Specialist II, Google Cloud (Fixed-Term Contract)

Google · Texas, United States

  • Hybrid
  • Full-time
  • $190,000 / year
  • Texas, United States

Job highlights

  • Lead large-scale compute projects for strategic clients.
  • Manage on-prem and cloud infrastructure integrations.
  • Liaise between clients and internal engineering.
  • Drive AI revolution with advanced Google Cloud tools.
  • Requires 5+ years infrastructure project experience.

About the role

Data Center Hardware Specialist II, Google Cloud (Fixed-Term Contract)

Google Cloud Consulting Professional Services guides customers through critical moments in their cloud journey to foster business growth. We empower businesses by leveraging Google’s global network, data centers, and software infrastructure. As part of an innovative and rapidly expanding team, you will contribute to shaping the future of businesses across all sizes, utilizing technology to enhance connections with customers, employees, and partners.

About the Role

As a Hardware Specialist, you will spearhead the technical delivery of highly confidential, large-scale compute projects for key clients. You will act as the central technical point of contact between global customers, internal engineering departments, and operations teams. Your responsibilities will include managing sophisticated on-premise and cloud-based environments, ensuring the seamless integration of high-performance accelerators with enterprise-grade networking and storage. This role is crucial for supporting the next generation of mission-critical, data-intensive workloads.

This is a remarkable opportunity to join Google Cloud’s Go-To-Market team and lead the global AI revolution for businesses. You will leverage Google's strong brand reputation, built on inventing foundational technologies proven at scale. We offer access to the world's most advanced AI portfolio, including cutting-edge Gemini models and the comprehensive Vertex AI platform, to help solve complex business challenges. Our collaborative culture provides direct interaction with DeepMind’s engineering and research talent, enabling you to effectively address customer needs. Join us to be a driving force behind our mission, ensure customer success, and define the new era of cloud computing.

Key Responsibilities

  • Maintain and oversee the end-to-end deployment of large-scale 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 execute successful technical solution implementations for high-density computing environments.
  • Partner with internal Specialists, Product, and Engineering teams to develop technical playbooks, best practices, and reference architectures for high-performance computing, influencing the roadmap for future hardware and software integration.
  • Engage with Sales and partners to manage project scope, priorities, deliverables, risks, issues, and timelines to ensure successful client outcomes.
  • Travel approximately 30% of the time for client engagements.

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.
  • 2 years of experience managing technical infrastructure within data center environments.
  • 2 years of experience cultivating client partnerships and managing cross-functional stakeholders.
  • Experience in hardware triage, diagnostics, and guiding repair workflows for server clusters and networks.

Preferred Qualifications

  • Master's degree or PhD in Computer Science or Engineering, or a related field.
  • Experience with networking and system design of load balancers, firewalls, and VPN in architecting, developing and maintaining production-grade systems.
  • Experience with end-to-end system architecture or accelerated computing hardware (e.g., Kubernetes, GKE, EKS, GPU workloads, or Linux-based distributed systems).
  • Experience managing strategic customer relationships and project stakeholders, including executive-level communication and influence on technical and operational decisions.
  • Expertise in maintaining clusters of massive-scale model training using high-end hardware accelerators and AI/ML infrastructure frameworks such as JAX, PyTorch, or OpenXLA.

Compensation

The US base salary range for this full-time position is $153,000-$222,000. Salary ranges are determined by role, level, and location. Individual pay is influenced by work location and other factors, including job-related skills, experience, and relevant education or training. Your recruiter can provide specific salary details for your preferred location during the hiring process. Please note that compensation details listed for US roles cover base salary only and do not include bonus, equity, or benefits.

Equal Opportunity Statement

Google is an equal opportunity workplace and affirmative action employer, committed to diversity and inclusion. We do not discriminate based on race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. We consider qualified applicants regardless of criminal histories, consistent with legal requirements. More information can be found in Google's EEO Policy and EEO is the Law. Applicants requiring accommodation due to a disability or special need should complete our Accommodations for Applicants form.

Key skills/competency

  • Data Center Hardware Specialist
  • Technical Solution Delivery
  • Project Management
  • Enterprise Infrastructure
  • Technical Architecture
  • Systems Administration
  • Cloud Environments
  • Data Center Infrastructure
  • Client Partnerships
  • Hardware Triage

Skills & topics

  • Data Center Hardware Specialist
  • Google Cloud
  • Technical Solution Delivery
  • Project Management
  • Enterprise Infrastructure
  • Technical Architecture
  • Systems Administration
  • Cloud Computing
  • Data Center Management
  • Hardware Triage
  • Networking
  • Accelerated Computing
  • AI Infrastructure
  • Remote
  • Texas

How to get hired

  • Tailor your resume: Highlight experience in data center hardware, cloud infrastructure, and project management. Quantify achievements where possible.
  • Craft a compelling cover letter: Express your enthusiasm for Google Cloud and how your skills align with the Data Center Hardware Specialist role.
  • Prepare for technical interviews: Brush up on hardware triage, diagnostics, networking, and cloud architecture principles.
  • Showcase stakeholder management: Be ready to discuss your experience managing client relationships and cross-functional teams.
  • Demonstrate problem-solving skills: Prepare examples of how you’ve diagnosed and resolved complex infrastructure issues.

Technical preparation

Master hardware triage and diagnostics for servers.,Understand cloud and on-prem infrastructure delivery.,Familiarize with accelerated computing hardware concepts.,Review networking principles: load balancers, firewalls.

Behavioral questions

Describe managing complex client infrastructure projects.,How have you managed cross-functional stakeholders?,Give an example of a critical hardware issue resolved.,How do you influence technical and operational decisions?

Frequently asked questions

What is the remote work policy for the Data Center Hardware Specialist role at Google Cloud?
This Data Center Hardware Specialist position is designated as remote, with the primary remote location specified as Texas, USA. Google embraces a hybrid workplace model, which includes fully remote roles.
What are the minimum educational and experience requirements for the Data Center Hardware Specialist II position?
Candidates need a Bachelor's degree in a technical field or equivalent experience. Minimum requirements include 5 years in technical solution delivery/project management, 4 years in technical architecture/systems administration, 2 years in data center infrastructure management, and 2 years in client/stakeholder management. Hardware triage experience is also essential.
What kind of projects will a Data Center Hardware Specialist work on at Google Cloud?
You will lead technical delivery for confidential, large-scale compute projects for strategic customers. This involves managing complex on-prem and cloud environments, integrating high-performance accelerators, and supporting data-intensive workloads for the next generation of mission-critical applications.
What are the preferred qualifications for the Data Center Hardware Specialist role?
Preferred qualifications include a Master's or PhD in Computer Science/Engineering, experience with networking and system design (load balancers, firewalls, VPNs), end-to-end system architecture, accelerated computing hardware (Kubernetes, GPUs), and managing executive-level client relationships. Expertise in AI/ML infrastructure frameworks is also highly valued.
How does Google Cloud support its employees in the Go-To-Market team for AI initiatives?
Google Cloud provides access to its advanced AI portfolio, including frontier Gemini models and the Vertex AI platform. Employees benefit from a collaborative culture with direct access to DeepMind's engineering and research talent to solve customer challenges.
What is the typical travel expectation for a Data Center Hardware Specialist at Google Cloud?
The role requires travel of approximately 30% of the time to engage with clients and manage project engagements.
How is the salary determined for the Data Center Hardware Specialist position at Google?
The US base salary range is $153,000-$222,000. The exact salary is determined by factors such as role, level, work location, job-related skills, experience, and education. Recruiters provide specific details during the hiring process.
Does the Data Center Hardware Specialist role involve working with AI/ML infrastructure?
Yes, expertise in maintaining clusters for massive-scale model training using high-end hardware accelerators and AI/ML infrastructure frameworks like JAX, PyTorch, or OpenXLA is a preferred qualification.