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Site Reliability Engineer, Managed AI at Crusoe Energy Systems LLC
Job Description
Crusoe's mission is to accelerate the abundance of energy and intelligence. We're crafting the engine that powers a world where people can create ambitiously with AI - without sacrificing scale, speed, or sustainability.
Be a part of the AI revolution with sustainable technology at Crusoe. Here, you'll drive meaningful innovation, make a tangible impact, and join a team that's setting the pace for responsible, transformative cloud infrastructure.
About the RoleAt Crusoe, our Site Reliability Engineering team ensures the reliability and scalability of Crusoe's AI-optimized cloud platform. We're looking for an SRE 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
- 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++)
- Familiarity with Kubernetes or container orchestration platforms
- Strong collaboration and communication skills
- Ability to thrive in a fast paced, mission driven environment
- Experience scaling inference or training workloads for LLMs
- Industry competitive pay
- Restricted Stock Units in a fast growing, well funded technology company
- Health insurance package options that include HDHP and PPO, vision, and dental for you and your dependents
- Employer contributions to HSA accounts
- Paid Parental Leave
- Paid life insurance, short term and long term disability
- Teladoc
- 401(k) with a 100% match up to 4% of salary
- Generous paid time off and holiday schedule
- Cell phone reimbursement
- Tuition reimbursement
- Subscription to the Calm app
- MetLife Legal
- Company paid commuter benefit; $300 per month
Compensation will be paid in the range of $204,000 - $247,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's education, experience, knowledge, skills, and abilities, as well as internal equity and alignment with market data.
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.
Typical mid-level pay: $133k for Software Developers nationally
Senior roles pay 64% more than entry—experience is well rewarded.
Strong candidate leverage
High demand and responsive wages. Negotiate confidently on all fronts.
Who this leverage applies to
Where to negotiate
Likely Possible Unlikely
Use competing offers and timing to your advantage.
Does this path compound?
Both the field and your earnings can grow significantly.
Good time to build expertise—demand will chase supply.