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Crux AI

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

Head of Pricing & Strategy

Corporate StrategyConfirmed live in the last 24 hours
Full-timePalo Alto, CA, USANo salary listed

About the Job

Requirements

  • 8–10+ years in pricing, commercial strategy, or infrastructure economics, including direct responsibility for pricing long-duration, high-value capacity contracts in cloud or accelerated compute, colocation, wholesale telecom, or power, and experience with performance-based or value-based pricing.
  • Have built a unit-economics or deal-profitability model that a company used to make binding decisions across finance, sales, and executives, and reconciled it against real operating data.
  • Have run deals from term sheet to signed contract and be comfortable with commercial terms including prepayment, credit, service-level agreements, take-or-pay, and pass-through costs.
  • Build skill files and models hands-on and take an outcome-driven approach to the work.
  • Be able to engage credibly with finance, sales, and engineering, including margin discussions with a chief financial officer, competitive discussions with a chief revenue officer, and cost-stack discussions with an infrastructure engineer.
  • Have a high tolerance for ambiguity and be able to navigate complexity.
  • Model multi-year asset economics and focus on long-run fleet economics, not only individual deals.
  • Build tools and use artificial intelligence and automation in everyday work to run analysis continuously.

Responsibilities

  • Build market intelligence on actual accelerated processing unit prices by generation, contract term, and region, and construct reference prices for Crux products based on terms, prepayment structures, customer credit ratings, and service-level agreement tiers.
  • Shape product pricing strategy using market intelligence, industry trends, competitive analysis, and demand and supply forecasting, including the mix and pricing of spot and long-term offerings and changes across generation transitions.
  • Run deal operations end to end, from term-sheet construction through negotiation support and contracting, to advance pricing, structure, and approvals.
  • Conduct customer analysis across segments, workload classes, willingness to pay, and value per use case to inform value-based pricing and capacity allocation.
  • Build the fully loaded cost and margin model of record and total-cost-of-ownership analysis for Sales, grounded in accelerator price/performance benchmarks and the value of products for specific customer use cases.
  • Lead deal economics on anchor contracts alongside the chief operating officer and chief financial officer, partnering with Sales, Finance, Demand/Supply Planning, Business Operations, and Strategic Supply/Partnerships.
  • Complete a first-cut fully loaded cost and margin model per accelerated processing unit-hour and per megawatt, projecting cost, price, and margin over multiple years and agreeing it with the chief financial officer as the basis of record.
  • Deliver a competitive pricing and capacity landscape across neoclouds, hyperscalers, and AI infrastructure providers, based on original market-price intelligence.
  • Publish reference price tables by term, prepayment, credit rating, and service-level agreement, and establish pricing architecture, rate structures by generation and commitment term, take-or-pay mechanics, pass-through costs, and approval frameworks for contracts above defined thresholds, anchored on deal-level profitability.
  • Establish a deal operations process with a standard term sheet, a path from term sheet to signed contract, and clear ownership at each step.
  • Price initial anchor customer contracts using the framework and run them from term sheet through contracting, including multi-year deal economics, margin, and scenario analysis for executive decision-making.
  • Put a customer-ready total-cost-of-ownership and price/performance narrative versus alternative accelerated compute into active Sales use, with value-based pricing tied to priority customer use cases.
  • Refresh market-price intelligence and the cost and margin model on a defined cadence, reconciling them against actuals, observed deal prices, and updated projections.
  • Deliver a customer-segment and workload-attractiveness assessment to inform Demand/Supply Planning and customer capacity allocation.
  • Build and deploy artificial-intelligence-enabled and automated skill files, models, and tools for pricing analysis, market intelligence, and scenario modeling.
  • Run pricing and deal operations as a repeatable function, with an automated deal-pricing tool supporting what-if scenarios, a rate card and reference price tables, approval thresholds, and a lightweight deal-review process.
  • Provide unit economics, profitability, market intelligence, and customer analysis as standing inputs to the executive team and board for strategic direction.
  • Model and navigate at least one accelerated processing unit generation transition in pricing and contract structure, including a forward view of how the next transition affects contract pricing and economics.

Desired Qualifications

  • Direct experience with accelerated compute economics, such as GPU or TPU capacity pricing, cluster total cost of ownership, or AI infrastructure financing.
  • Top-tier strategy consulting followed by an operating role in cloud, data centers, or energy.
  • Experience preparing pricing or market materials for board or sponsor audiences.

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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