Staff Site Reliability Engineer
Crusoe
Staff Site Reliability Engineer
Crusoe
Builds AI data centers near cheap energy
Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.
We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.
We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.
If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.
About the Role:
At Crusoe, our Site Reliability Engineering team ensures the reliability and scalability of Crusoe’s AI-optimized cloud platform. We’re looking for a Staff Site Reliability Engineer with a strong background in distributed systems and hands-on experience with large language models to help us build and operate managed AI services at scale. This role is central to delivering highly available, performant, and cost-efficient AI infrastructure that powers compute-intensive, latency-sensitive workloads for our customers.
What You’ll Work On:
Design and operate reliable managed AI services with a focus on serving and scaling LLM workloads
Build automation and reliability tooling to support distributed AI pipelines and inference services
Define, measure, and improve SLIs/SLOs across AI workloads to ensure performance and reliability targets are met
Collaborate with AI, platform, and infrastructure teams to optimize large-scale training and inference clusters
Automate observability by building telemetry and performance tuning strategies for latency-sensitive AI services
Investigate and resolve reliability issues in distributed AI systems using telemetry, logs, and profiling
Contribute to the architecture of next-generation distributed systems purpose-built for AI-first environments
What You’ll Bring:
Strong software engineering background — experience building production-grade systems beyond scripting or Bash
Demonstrated experience in distributed systems design and implementation
Hands-on work with large language models (LLMs) or AI/ML infrastructure
SRE mindset and experience (whether or not under the SRE title) including:
Defining and measuring SLIs/SLOs
Building monitoring and observability systems
Driving performance and reliability improvements
Designing fault-tolerant systems and automated testing strategies
Proficiency in at least one modern programming language (Python, Go, Java, C++)
Deep working knowledge of Kubernetes (cluster architecture, networking, scheduling, and workload management)
Strong collaboration and communication skills
Ability to thrive in a fast-paced, mission-driven environment
Bonus Points:
Experience scaling inference or training workloads for LLMs
Benefits:
Crusoe also offers a competitive benefits package designed to support financial security, health, and overall well-being. Our benefits are tailored to local market standards and include core offerings such as pension contributions and additional perks to support work-life balance.
Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
Crusoe builds and runs data centers for artificial intelligence, placing them near cheap or otherwise wasted energy and handling everything from the power supply to the cloud software. It developed the flagship campus in Abilene, Texas, for Stargate, the AI infrastructure project backed by OpenAI and Oracle. AI companies rent its GPU servers on demand or under longer contracts through Crusoe Cloud to train and run their models, while larger customers lease entire campuses that Crusoe develops and operates for them. The company was founded in 2018, when it began running computers at oil fields on natural gas that would otherwise have been burned off, and it is based in Denver.
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