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Crux AI

Compute-as-a-service platform for large AI workloads

Vice President Compute

Engineering LeadershipConfirmed live in the last 24 hours
Full-timePalo Alto, CA, USA

About the Job

Requirements

  • 15+ years building and operating large-scale compute or cloud infrastructure platforms, including 7+ years leading organizations of organizations at the SVP level or above.
  • Direct ownership of a production compute platform at scale, such as a hypervisor or virtualization platform, a bare metal or dedicated cloud, a hyperscale compute service, or accelerator (TPU, GPU, or custom silicon) infrastructure, with accountability for reliability and customer outcomes.
  • A track record of leading a platform rebuild or transformation while keeping existing customers running.
  • Ability to work hands-on and discuss scheduler design, failure domains, and provisioning bottlenecks with engineers, then communicate those topics to the board.
  • Experience owning AI-first engineering teams and making roadmap tradeoffs that balance customer value, cost, and reliability.
  • Ability to navigate ambiguity and complexity.
  • Ability to evaluate cluster readiness through acceptance under customer-shaped load and design systems that make incidents less disruptive.
  • Ability to go deep into engineering implementations.
  • Fluency with AI agents, or commitment to becoming fluent quickly, and ability to embed agentic workflows as first principles before adding headcount or process.

Responsibilities

  • Define the compute platform strategy and architecture of record, including how TPU capacity is divided into dedicated clusters, provisioned, isolated, and delivered to customers.
  • Architect and deliver the full compute lifecycle, including hardware onboarding and inventory, operating system and firmware provisioning, burn-in and validation, rack certification, customer handoff, repair, and retirement.
  • Design and ship managed container orchestration on bare metal, including automated control-plane provisioning, upgrades, and operators for TPUs.
  • Build and lead a multi-layer engineering organization spanning cluster provisioning and lifecycle, orchestration and scheduling, fleet health and telemetry, and the customer-facing compute surface.
  • Hire engineering leaders and maintain close awareness of team execution and emerging issues.
  • Own compute reliability and efficiency end to end, including service-level objectives, goodput and utilization, time from rack-ready to customer-ready, and fleet-scale failure recovery.
  • Serve as the primary technical counterpart to Google on the TPU hardware, software, and services roadmap, translating customer needs into Google requirements and Google capabilities into Crux product.
  • Set the build, adopt, or integrate direction for the compute software stack, determining what Crux builds natively, adopts from Google, or sources from partners.
  • Establish security, tenant isolation, and compliance for dedicated compute serving sovereign and regulated customers.
  • Partner with Data Center Engineering and Capacity Delivery on cluster design, bring-up, and acceptance; Network Engineering on fabric and interconnect; technical program managers on commitments and timing; and Finance on utilization, failure-rate, and spares inputs to the cost and margin model.
  • Understand the TPU platform, Google partnership model, capacity plan, and initial customer commitments, and publish a written compute architecture and organization plan.
  • Hire or commit the first layer of engineering leaders across core compute domains.
  • Establish working cadences with Google counterparts, Data Center Engineering, Network Engineering, and customers’ engineering and product teams.
  • Triage appropriately and continuously improve the function.
  • Establish AI-forward development of the zero-touch provisioning, orchestration, and observability stack.
  • Deliver the first production TPU clusters through provisioning, validation, and customer handoff on the committed timeline.
  • Define and instrument compute service-level objectives, utilization, and time-to-capacity metrics, and review them weekly in a format trusted by the executive team.
  • Ship the first version of the customer-facing compute surface, including access, APIs, and observability, for customers to use independently.
  • Build AI-enabled fleet-operations tools hands-on for daily team use.
  • Run a multi-site TPU fleet at customer-committed reliability and efficiency targets.
  • Build a high-performing compute organization with strong leaders in every domain and maintain hiring standards as the team grows.
  • Make the compute platform a differentiator in customer wins and renewals, and agree on the roadmap for future capacity phases with Google and the executive team.

Desired Qualifications

  • Compute leadership at a hyperscaler or neocloud.
  • Hands-on exposure to AI accelerators or high-performance computing, including supercomputing, accelerator software stacks, or large training and inference clusters.
  • Experience building sovereign, distributed, or on-premises cloud offerings for regulated and government customers.
  • Experience in both startup and scaled enterprise environments, including building an organization from its first hires.
  • Standing in open infrastructure communities such as the Open Compute Project or OpenStack, or patents in systems and infrastructure.

About the Company

Crux AI

Compute-as-a-service platform for large AI workloads

Crux AI offers compute-as-a-service for large-scale AI workloads by combining power, high-density data centers, networking, and accelerated computing into a single managed platform. It uses Google’s TPU hardware and software, with Crux AI acting as the single accountable partner from long-term capacity planning to production deployment. The company differentiates itself by delivering a reliability-engineered TPU-based infrastructure backed by Google and Blackstone, focused on end-to-end, turnkey management rather than generic cloud services. Its goal is to help customers scale demanding AI workloads with an enterprise-grade, dependable infrastructure and support.

Company size
1-10
Company stage
Debt Financing
Total funding
$22B
Headquarters
Palo Alto, CA
Founded
2026

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