Staff Solutions Engineer

Crusoe Cloud is seeking a Staff Solutions Engineer to work closely with our most strategic enterprise customers deploying AI/ML workloads on Crusoe's high-performance GPU infrastructure. This is a hands-on, customer-facing role requiring deep technical expertise in Kubernetes, MLOps, and cloud infrastructure.

You'll guide customers through end-to-end deployment—owning the PoC process, optimizing workloads post-sale, and serving as a critical technical voice between our customers and engineering teams. Ideal candidates are passionate about AI infrastructure, fluent in containerized environments, and confident translating workloads across cloud platforms.

• Customer Enablement: Lead technical onboarding and deployment of complex AI/ML workloads with strategic enterprise customers—owning the PoC through to post-sales optimization.
• Kubernetes + MLOps Focus: Architect and deploy ML workloads using Kubernetes-based stacks (e.g., Ray, Kubeflow). Design infrastructure that balances performance, scalability, and efficiency.
• Infrastructure-Centric Thinking: Go beyond abstracted services—deploy and optimize AI/ML workloads directly on Crusoe infrastructure. Ensure performance at the container and hardware level.
• Cross-Cloud Translation: Help customers migrate and adapt workloads across AWS, Azure, and GCP. Understand and explain the tradeoffs between cloud-native and Crusoe-native approaches.
• Technical Storytelling: Conduct workshops, live demos, and solution reviews. Contribute to case studies, solution briefs, and blog posts that highlight real-world customer success.
• Voice of the Customer: Relay feedback to internal engineering and product teams to continuously improve Crusoe's platform based on real-world implementation experience.

• Deep Kubernetes Expertise: 3-5 years building and deploying containerized workloads. Experience with Helm, Terraform, Docker, and multi-node orchestration a must.
• MLOps Deployment Experience: Demonstrated success deploying ML frameworks (e.g., Ray, MLflow, Airflow) on Kubernetes—especially for inference and model training workflows.
• Hands-on Cloud Infrastructure Knowledge: Familiarity with compute, storage, networking, and scaling in AWS, GCP, or Azure. Experience translating workloads across clouds is highly desirable.
• Customer-Facing Technical Confidence: Able to navigate stakeholder conversations, gather requirements, lead technical engagements, and support customers in both pre- and post-sales environments.
• Strong Linux and CLI Proficiency: Comfortable operating in Linux environments and troubleshooting infrastructure issues via CLI.
• Collaborative Energy: Strong communication skills and eagerness to partner cross-functionally with Engineering, Product, and Sales to make customers successful.

• Experience with Ray, Kubeflow, or other distributed ML orchestration platforms
• Exposure to Slurm, but with a primary focus on containerized MLOps over traditional HPC
• Multi-cloud deployment or migration experience (especially AWS → Crusoe transitions)
• Content contributions (tech talks, blogs, public case studies)
• Must be able to pass a background check
• Embod the Company values

Crusoe offers a competitive benefits package designed to support financial security, health, and overall well-being, including pension contributions, private health and dental insurance, income protection, life assurance and more.

Compensation will be paid as salary or hourly. Compensation to be determined by the applicant's education, experience, knowledge, skills, and abilities, as well as internal equity and alignment with market data.

Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.