Senior Production Engineer (Managed AI)

Join Crusoe Energy, a leading company in the AI infrastructure space. As a Senior Production Engineer, you will be responsible for designing and operating reliable managed AI services, building automation and reliability tooling, and collaborating with various teams to optimize large-scale training and inference clusters. You will also contribute to the architecture of next-generation distributed systems purpose-built for AI-first environments. Enjoy comprehensive health benefits, paid time off, a 401(k) matching program, and resources for mental wellness.

• 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.
• Collaborate with AI, platform, and infrastructure teams to optimize large-scale training and inference clusters.
• 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
• Demonstrated experience in distributed systems design and implementation
• Hands-on work with large language models (LLMs) or AI/ML infrastructure
• Strong software engineering background — experience building production-grade systems beyond scripting or Bash
• Familiarity with Kubernetes or container orchestration platforms
• Driving performance and reliability improvements
• Designing fault-tolerant systems and automated testing strategies
• Strong collaboration and communication skills
• Proficiency in at least one modern programming language (Python, Go, Java, C++)
• Ability to thrive in a fast-paced, mission-driven environment
• SRE mindset and experience (whether or not under the SRE title) including:
• Defining and measuring SLIs/SLOs
• Building monitoring and observability systems
• Experience scaling inference or training workloads for LLMs