Site Selection Engineer

Crusoe · Data AI · San Francisco, CA - US · Data Center Operations (DIG)

This role focuses on the technical and commercial evaluation of global data center expansion for AI workloads. The engineer will bridge GPU engineering requirements with the colocation market, leading deal execution, lease negotiation, SLA development, TCO modeling, and technical due diligence for high-density GPU deployments. The goal is to ensure leased power is technically capable and commercially structured for Crusoe's long-term interests.

What you'd actually do

  1. Lead Commercial Negotiations: Drive the execution of Letters of Intent (LOIs) and definitive Leases (Master Lease Agreements/Service Orders). Negotiate power ramp schedules, expansion options, termination rights, and holdover clauses.
  2. Author and negotiate rigorous Service Level Agreements. Define critical parameters for uptime, temperature/humidity envelopes (including liquid cooling/DLC requirements), PUE guarantees, and liquidated damages for delivery delays.
  3. Build comprehensive Total Cost of Ownership models that account for base rent, metered power, PUE premiums, operating expenses, and local tax abatements (e.g., Texas HB 1223).
  4. Perform deep-dive technical due diligence on provider sites. Review one-line diagrams, P&IDs, and floor plans to verify redundancy levels (N+1/2N), fiber latency, and structural floor loading.
  5. Assess provider readiness for high-density GPU deployments (50kW–1,000kW+ per rack), including cooling loop capacities, water availability for RDHx/DLC, and power busway limits.

Skills

Required

  • 3–7 years in Data Center Site Selection, Infrastructure Strategy, or Data Center Engineering/Development.
  • Ability to interpret electrical/mechanical engineering drawings and translate technical constraints into commercial lease protections.
  • Proven track record of redlining SLAs and negotiating business terms with Tier-1 colocation providers (Equinix, Digital Realty, Vantage, etc.).
  • Advanced financial modeling skills in Excel; ability to structure complex "buy vs. lease" and "CAPEX vs. OPEX" scenarios.
  • Deep understanding of data center power structures (Gross vs. NNN), utility interconnection processes, and regional tax incentive programs.
  • Bachelor’s degree in Engineering (Electrical/Mechanical), Finance, or Real Estate.

Nice to have

  • problem-solving
  • opportunity-finding
  • sense of urgency
  • growth mindset

What the JD emphasized

  • high-density GPU deployments
  • liquid cooling/DLC requirements
  • high-density GPU deployments