Crusoe
AI infrastructure
Senior+SolutionsEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior+ Solutions Engineer at Crusoe. Skills: Kubernetes, MLOps, Cloud infrastructure, AI/ML workloads. Lead technical onboarding. Deploy complex AI/ML workloads”
What You'll Achieve.
Accelerate abundance of energy and intelligence; Power world's most ambitious AI workloads; Help customers and partners advance their AI strategies; Make customers successful; Continuously improve Crusoe’s platform
Industry & Context.
Problem-solving
Must be able to pass a background check
What They're Looking For.
Must Have
3-5 years building and deploying containerized workloads, Experience with Helm, Experience with Terraform, Experience with Docker, Multi-node orchestration experience, Demonstrated success deploying ML frameworks on Kubernetes, Familiarity with compute, storage, networking, and scaling in AWS, GCP, or Azure, Customer-facing technical confidence, Linux proficiency, CLI proficiency, Communication skills, Ability to pass a background check
Nice to Have
Experience translating workloads across clouds, Experience with Ray, Experience with Kubeflow, Experience with distributed ML orchestration platforms, Exposure to Slurm, Multi-cloud deployment or migration experience, Content contributions (tech talks, blogs, public case studies)
What You'll Do.
Lead technical onboarding
Deploy complex AI/ML workloads
Optimize workloads post-sale
Architect and deploy ML workloads
Design infrastructure
Deploy and optimize AI/ML workloads
Ensure performance at container and hardware level
Migrate and adapt workloads across clouds
Conduct solution reviews
Contribute to case studies
Contribute to solution briefs
Contribute to blog posts
Relay feedback to engineering and product teams
How You'll Work.
Team & Collaboration
Partner cross-functionally with Engineering, Product, and Sales; Serve as technical voice between customers and engineering teams
Communication Scope
Customer-facing technical confidence; Technical Storytelling; Communication skills
Process & Methodology
Own the PoC process
Full Job Description
Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster. We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI. We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services. If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe. About This Role: Crusoe Cloud is seeking a Senior+ 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. What You'll Be Working On: - Customer Enablement: Lead technical onboarding and deployment of complex AI/ML workloads with strategic enterprise
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