Senior AI Infra Engineer - Scalable LLM Platforms

Crusoe Energy Systems LLC; San Francisco, Northern (CA, KY); Hybrid; USD 170,000 - 205,000; Full time

Benefits offered by this job

Health insurance

401(k) with company match

Paid parental leave

Life insurance

Vision and dental

Teladoc

Commuter benefit

Tuition reimbursement

Generous PTO

Job summary

Crusoe Energy Systems LLC in San Francisco is seeking a Senior Production Engineer with a strong background in distributed systems and hands-on experience with large language models to help build and operate managed AI services at scale.

You will design and run reliable AI services, implement automation and observability, and work with AI, platform, and infrastructure teams to improve performance and reliability of latency-sensitive workloads.

Qualifications

• Proven experience building production-grade distributed systems.
• Hands-on work with LLMs or AI/ML infrastructure.
• Strong SRE practices including SLIs/SLOs.

Responsibilities

• 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.

Skills

Distributed systems

LLM infrastructure

Python/Go/Java/C++

Observability/monitoring

Cloud platforms

Tools

Kubernetes

Job description

Crusoe Energy Systems LLC in San Francisco is seeking a Senior Production Engineer with a strong background in distributed systems and hands-on experience with large language models to help build and operate managed AI services at scale.

You will design and run reliable AI services, implement automation and observability, and work with AI, platform, and infrastructure teams to improve performance and reliability of latency-sensitive workloads.