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Staff Instrumentation & Controls Engineer, Deployment at Crusoe - ApplyBlast

Staff Instrumentation & Controls Engineer, Deployment

Crusoe

3 months ago

3.7 on Glassdoor

Amarillo, TX

Hybrid

Full Time

Senior

0 applicants

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About this role

As a Staff Instrumentation and Controls Engineer at Crusoe, you will lead the deployment and integration of Building Management Systems (BMS), Energy Management Systems (EPMS), and SCADA solutions for hyperscale AI data centers. This role requires bridging engineering design with on-site field execution to ensure the seamless operation of critical HVAC, electrical, and monitoring infrastructure. You will drive complex rollouts, oversee contractor integration, and establish deployment standards to support the company's energy-first approach to AI compute.

Responsibilities

Lead field deployment and integration of BMS and EPMS automation solutions
Enforce system standards and deployment patterns across multiple data center sites
Configure dashboards and HMIs for operator visibility of building and power systems
Oversee system integrators during deployments and resolve complex automation issues
Conduct Factory Acceptance Testing and Site Acceptance Testing for system validation

Skills

Qualifications

Bachelor's degree in Electrical EngineeringBachelor's degree in Controls EngineeringBachelor's degree in Computer EngineeringIgnition CertificationRockwell Certification

About Crusoe

crusoe.ai

Headquarters

Denver, Colorado, United States

Company Size

201-500 employees

Founded

2018

View Profile

Crusoe is the AI factory company, designing, building, and operating next-generation AI infrastructure including a cloud platform, managed inference services, and modular AI data centers. Using an energy-first approach powered by sources such as wind, solar, hydropower, geothermal, and natural gas with carbon capture, Crusoe enables businesses to deploy AI workloads at scale with high performance and 24/7 enterprise support. The company offers purpose-built GPU compute, managed Kubernetes and Slurm clusters, and a proprietary inference engine optimized for large-context AI workloads.