Energy Full-time

Senior Engineer, Load Integration & Model Development

Crusoe

Posted

Jun 04, 2026

Location

Remote (US)

Type

Full-time

Compensation

$175000 - $210000

Mission

What you will drive

  • Perform and support comprehensive grid integration studies for large-load facilities within MISO and PJM.
  • Manage transmission injection processes and perform load deliverability studies to ensure grid stability and capacity.
  • Strategize Points of Interconnection (POIs) based on evolving business needs and changing regulatory requirements.
  • Contribute to the technical development of the team, sharing expertise and best practices in grid integration and ISO/RTO navigation.

Impact

The difference you'll make

This role enables the expansion of energy infrastructure to power AI workloads, accelerating the transition to sustainable and reliable energy systems while supporting cutting-edge AI innovation.

Profile

What makes you a great fit

  • Masterโ€™s degree in Power Systems with 3+ years of experience, or a Bachelorโ€™s degree with 7+ years of experience in Power Systems.
  • Deep experience in grid planning, system modeling, and grid code compliance studies.
  • Strong working knowledge of MISO/SPP transmission topology and load interconnection methodologies.
  • Excellent technical report writing and verbal communication skills.

Benefits

What's in it for you

  • Industry competitive pay
  • Restricted Stock Units
  • Health insurance (HDHP and PPO), vision, dental
  • Employer contributions to HSA accounts
  • Paid Parental Leave
  • Paid life insurance, short-term and long-term disability
  • Teladoc
  • 401(k) with 100% match up to 4% of salary
  • Generous paid time off and holiday schedule
  • Cell phone reimbursement
  • Tuition reimbursement
  • Subscription to Calm app
  • MetLife Legal
  • Company paid commuter benefit ($300/month)
  • Compensation: $175,000 - $210,000

About

Inside Crusoe

Crusoe is a vertically integrated AI infrastructure company that owns and operates each layer of the stack from electrons to tokens, with an energy-first approach to power AI workloads sustainably.