Staff Site Reliability Engineer: AI Infra for LLMs at Scale

Crusoe; United States; Hybrid; USD 180,000 - 280,000; Full time

Job summary

Crusoe is hiring a Staff Site Reliability Engineer to build and operate AI-optimized cloud services. You will shape reliability, scalability, and cost efficiency for latency-sensitive AI workloads powering customer workloads.

You will work with a team spanning AI, platform, and infrastructure, delivering highly available, production-grade systems and automation at scale. Remote-friendly, fast-paced, high-impact environment.

Qualifications

• Strong software engineering background building production-grade systems
• Experience designing and implementing distributed systems
• Hands-on with LLMs or AI/ML infrastructure
• SRE mindset: defining and measuring SLIs/SLOs, observability, testing
• Proficiency in at least one modern programming language (Python/Go/Java/C++)
• Deep knowledge of Kubernetes (architecture, networking, scheduling)
• Excellent collaboration and communication skills
• Thrives in a fast-paced, mission-driven environment

Responsibilities

• Design and operate reliable managed AI services focusing on LLM workloads
• Build automation and reliability tooling for distributed AI pipelines and inference services
• Define, measure, and improve SLIs/SLOs for AI workloads
• Collaborate with AI, platform, and infrastructure teams to optimize clusters
• Automate observability with telemetry and performance tuning for latency-sensitive AI services
• Investigate and resolve reliability issues in distributed AI systems using telemetry and logs
• Contribute to architecture of next-generation distributed AI systems

Skills

Distributed systems

Production-grade software

LLM/AI infra

SRE mindset

Python

Go

Java

C++

Kubernetes

Collaboration

Fast-paced environment

Tools

Kubernetes

Job description

Crusoe is hiring a Staff Site Reliability Engineer to build and operate AI-optimized cloud services. You will shape reliability, scalability, and cost efficiency for latency-sensitive AI workloads powering customer workloads.

You will work with a team spanning AI, platform, and infrastructure, delivering highly available, production-grade systems and automation at scale. Remote-friendly, fast-paced, high-impact environment.