DevOps Lead Architect
AuraFull Time
Senior (5 to 8 years)
Key technologies and capabilities for this role
Common questions about this position
This is an onsite position.
This information is not specified in the job description.
The role requires a Bachelor’s degree in Electrical Engineering, Controls Engineering, Computer Science, or related discipline, extensive experience in automation system architecture including PLC, SCADA, BMS, and EPMS platforms, background in BMS/EPMS, SCADA, or ICS systems ideally in data centers, familiarity with protocols like BACnet, Modbus, OPC-UA, MQTT, and strong knowledge of HVAC, electrical systems, PLC/DDC logic, and industrial automation.
Crusoe focuses on accelerating energy and intelligence abundance, driving meaningful innovation in sustainable AI technology, making tangible impact, and setting the pace for responsible, transformative cloud infrastructure.
A strong candidate will have extensive experience in designing scalable automation frameworks and custom UIs for mission-critical environments, particularly in data centers, along with proven ability to translate operational needs into robust architecture, leadership in mentoring teams, and deep knowledge of control protocols and systems.
Utilizes wasted energy for computing power
Crusoe Energy Systems Inc. provides digital infrastructure that focuses on using wasted, stranded, or clean energy sources to power high-performance computing and artificial intelligence. The company helps clients in the technology and energy sectors by offering scalable computing solutions that aim to reduce greenhouse gas emissions and support the transition to cleaner energy. Crusoe's approach involves converting excess natural gas and renewable energy into computing power, which allows them to maximize resource efficiency while minimizing environmental impact. Unlike many competitors, Crusoe specifically targets the intersection of energy and technology, generating revenue by supplying computing resources to enterprises that need significant computational power for applications like AI and machine learning, along with providing technical support.