Senior AI Infra Production Engineer (LLM & Distributed Systems)

Fdetimes; San Francisco (CA); On-site; USD 170,000 - 205,000; Full time

Benefits offered by this job

Industry competitive pay

Restricted Stock Units (RSUs)

Health insurance

401(k) with match

Parental Leave

Life insurance

Job summary

Crusoe is seeking a Senior Production Engineer to scale our AI-optimized cloud platform. You will design and operate reliable services for serving and scaling LLM workloads, building automation, and improving observability across distributed AI pipelines.

You should bring strong software engineering, experience with LLMs or AI infrastructure, and proficiency in Python/Go/Java/C++. Familiarity with Kubernetes is a plus.

Qualifications

• Strong software engineering background with production-grade systems
• Experience with distributed systems design and implementation
• Hands-on work with LLMs or AI/ML infrastructure
• SRE mindset including defining and measuring SLIs/SLOs, building monitoring/observability
• Proficiency in Python, Go, Java or C++
• Familiarity with Kubernetes or container orchestration platforms

Responsibilities

• Design and operate reliable managed AI services focused on serving and scaling 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 large-scale training and inference clusters
• Automate observability with telemetry and performance tuning for latency-sensitive AI services
• Investigate and resolve reliability issues in distributed AI systems
• Contribute to architecture of next-generation distributed systems for AI-first environments

Skills

Distributed systems design

SRE mindset

LLM infrastructure

Python

Go

Java

C++

Docker

Kubernetes

Collaboration

Tools

Kubernetes

Job description

Crusoe is seeking a Senior Production Engineer to scale our AI-optimized cloud platform. You will design and operate reliable services for serving and scaling LLM workloads, building automation, and improving observability across distributed AI pipelines.

You should bring strong software engineering, experience with LLMs or AI infrastructure, and proficiency in Python/Go/Java/C++. Familiarity with Kubernetes is a plus.