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CrusoeCrusoe

Senior Production Engineer

As a Senior Production Engineer, you will ensure the reliability and scalability of Crusoe’s AI-optimized cloud platform, focusing on designing and operating managed AI services for LLM workloads. You will build automation and reliability tooling, define SLIs/SLOs, and optimize large-scale training and inference clusters.

About the job

About the Role:

At Crusoe, our Production Engineering team ensures the reliability and scalability of Crusoe’s AI-optimized cloud platform. We’re looking for a Senior Production 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++)
  • Familiarity with Kubernetes or container orchestration platforms
  • 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:

  • 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:

Compensation will be paid in the range of $209,000 - $253,000. 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.

Skills

Distributed Systems, LLMs, Kubernetes, Python, Go, Java, C++, SRE, Monitoring, Observability

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