Crusoe
Data AI · GPU cloud / AI infra
- HQ
- Denver, US
- Founded
- 2018
- Website
- crusoe.ai
Crusoe currently has 14 active AI-related job listings. The majority of these roles are focused on serving infrastructure, accounting for 36% of the openings, followed closely by roles in agents and post-training, each representing 29%. Engineering is the primary function being hired for, with 13 positions available, while Product has one opening. Frequent technical tags include model serving, inference infrastructure, and fine-tuning, suggesting a focus on AI model deployment and optimization. Over the last 30 days, Crusoe has posted 2 new AI roles, a 50% decrease compared to the previous 30-day period.
Currently tracking 12 active AI roles, with 98 new openings in the last 4 weeks. Primary focus: Serve · Engineering. Salary range $172k–$355k (avg $249k).
Crusoe currently has 20 active AI-related roles in our index. The most common open titles are: Enterprise IT Architect, Principal Systems Software Engineer, Senior Director, AI Model LifeCycle, Senior Engineering Manager, Managed Platform Services, Senior Engineering Manager, Management Plane Systems. Most positions are in Engineering and Product.
Crusoe's active AI hiring is concentrated in: serving infrastructure (50%), agents (25%), post-training (20%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Crusoe is hiring AI talent in: United States (1 role).
Job postings at Crusoe most frequently reference: model serving, inference infra, llm observability, fine tuning, agent orchestration.
In the past 30 days, Crusoe has posted 5 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Staff Product Manager, Managed Intelligence (SF/Sunnyvale) Product Manager for Crusoe Cloud's Managed Intelligence services, focusing on defining, building, and scaling AI and agentic capabilities. The role involves strategic roadmap execution, market growth, customer advocacy, and defining the model lifecycle from data ingestion to inference and agentic workflows, bridging research and product for AI-native companies. | AgentPost-train | 9 |