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Site Reliability Engineer
Crusoe Energy · Tel Aviv - IL · Posted 2 days ago
"Shape the reliability of an AI-first cloud platform, defining SLOs and tooling for LLM inference and training clusters at scale."
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
- 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
- Experience scaling inference or training workloads for LLMs
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