VP, Compute Greater San Jose, CA Area

Built to set the gold standard for integrated AI infrastructure

Crux AI is a newly formed, U.S.-based integrated AI infrastructure company created to remove the physical and operational constraints on consequential AI ambitions. Crux brings together power, high-density data centers, TPU silicon, networking, orchestration software, and ongoing operations as one integrated system.

Crux is being capitalized to plan every layer together, develop each one to demanding standards, and operate the whole system with efficiency and reliability. That gives hyperscalers, frontier AI labs, sovereign customers, enterprises, and AI-native companies greater freedom to pursue the AI they are here to create.

WHAT YOU'LL DO

You will own compute at Crux: the platform that turns Google TPUs, Crux power and data center capacity, and our network into dedicated, reliable, customer-ready AI compute. Reporting to our CTPO, you own everything between the rack and the customer's first job: the TPU cluster fleet, the software that provisions, monitors and heals it, the container orchestration layer that schedules work onto it, and the compute products our customers consume, from our first phase of capacity through a multi-gigawatt fleet.

This is a platform-builder seat: you will set the architecture of record, hire the leaders, and hold the bar for reliability, efficiency, and speed as Crux scales.

In this role, you will:

Define the compute platform strategy and architecture of record: how TPU capacity is carved into dedicated clusters, provisioned, isolated, and delivered to hyperscalers, frontier AI labs, sovereign customers, and enterprises.

Architect and deliver the full compute lifecycle: hardware onboarding and inventory, OS and firmware provisioning, burn-in and validation, rack certification, customer handoff, repair and retirement.

Design and ship Crux's managed container orchestration on bare metal: 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 people better than you at their craft, then stay close enough to know when something is off before it shows up in a report.

Own compute reliability and efficiency end to end: SLOs, goodput and utilization, time from rack-ready to customer-ready, and failure recovery at fleet scale, achieved through discipline, not heroics.

Serve as Crux's 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 line for the compute software stack: what Crux builds natively, what it adopts from Google, and what it sources from partners.

Stand up the security, tenant isolation, and compliance posture that sovereign and regulated customers require for dedicated compute.

Partner with Data Center Engineering and Capacity Delivery on cluster design, bring-up, and acceptance; with Network Engineering on fabric and interconnect; with TPM's on what we can commit to and when; and with Finance on the utilization, failure-rate, and spares inputs to the cost and margin model of record.

SIGNALS OF SUCCESS

After 60 days in this role:

Gained a complete understanding of the TPU platform, the Google partnership model, the capacity plan of record, and our first customer commitments, and published a written compute architecture and org plan.

Hired or committed your first layer of engineering leaders across the core compute domains.

Established working cadences with Google counterparts, Data Center Engineering, Network Engineering, and our customers’ engineering and product teams.

Adapted to a fast-paced environment, triaging appropriately and continuously improving our function.

Stood up AI-forward development of the zero-touch provisioning, orchestration and observability stack

After 6 months:

Delivered the first production TPU clusters through provisioning, validation, and customer handoff on the committed timeline.

Defined and instrumented compute SLOs, utilization, and time-to-capacity metrics, reviewed weekly in a format the executive team trusts.

Shipped the first version of the customer-facing compute surface (access, APIs, observability) that customers use without hand-holding.

Demonstrated an AI-forward and automated approach to this role: you have built, in a hands-on way, AI-enabled tools for fleet operations that the team uses every day.

After 1 year:

Running a multi-site TPU fleet at the reliability and efficiency targets committed to customers, with incidents becoming rarer and more boring.

Built a high-performing compute organization with strong leaders in every domain and a hiring bar that holds as the team grows.

Made the compute platform a differentiator in customer wins and renewals, with the roadmap for the next phases of capacity agreed with Google and the executive team.

EXPERIENCES, ATTRIBUTES AND MINDSET THAT INDICATE A GOOD MATCH

Experiences

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 (on-prem to cloud, legacy to modern architecture, or a new platform from zero to meaningful revenue) while keeping existing customers running.

Attributes

You are outcome driven and hands-on. You can go deep on scheduler design, failure domains, or a provisioning bottleneck with your engineers, then take the same topic to the board. This is a builder's seat, not a supervisory one.

You have owned AI-first engineering teams, and you make roadmap tradeoffs with customer value, cost, and reliability in the same frame.

You have a high tolerance for ambiguity. You absorb ambiguity and navigate complexity rather than passing it along.

Mindset

You are skeptical by default. "The cluster is ready" is a hypothesis until it passes acceptance under customer-shaped load. You build the system that makes the next incident boring.

You operate as an owner, not a supervisor.

You like to build and are not afraid to go deep into engineering implementations

You are AI-agentic first. Fluent with AI agents, or committed to becoming so quickly, you embed them as first principles in how you and your team work, defaulting to agentic workflows before adding headcount or process.

Nice to have (Preferred, not required):

Compute leadership at a hyperscaler (Google Cloud, AWS, Microsoft Azure, Meta Infrastructure) or a neocloud (CoreWeave, Nebius, Lambda, Crusoe).

Hands-on exposure to AI accelerators or high-performance computing: supercomputing, accelerator software stacks, or large training and inference clusters.

Experience building sovereign, distributed, or on-prem 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 (for example, Open Compute Project or OpenStack) or patents in systems and infrastructure.

Salary Range Information

The annual salary range for this position has been estimated based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.

About Crux

We offer generous base, bonus and additional incentive based compensation

Health, dental, and vision coverage for you and your dependents

Company-paid life insurance and disability

Full suite of other optional benefits

401(k) Plan with 4% company match

Hybrid schedule offering four days in-office collaboration paired with one remote workday for focused, individual work