Senior to Senior Staff Solutions Engineer

Crusoe • Sunnyvale, CA

57d • $175,000 - $250,000

About The Position

Crusoe Cloud is seeking a Sr. to Senior Staff level 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.

Requirements

• Deep Kubernetes Expertise: 7+ 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.

Nice To Haves

• 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)

Responsibilities

• 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.

Benefits

• Industry competitive pay
• Restricted Stock Units in a fast growing, well-funded technology company
• Health insurance package options that include HDHP and PPO, vision, and dental for you and your dependents
• Employer contributions to HSA accounts
• Paid Parental Leave
• Paid life insurance, short-term and long-term disability
• Teladoc
• 401(k) with a 100% match up to 4% of salary
• Generous paid time off and holiday schedule
• Cell phone reimbursement
• Tuition reimbursement
• Subscription to the Calm app
• MetLife Legal
• Company paid commuter benefit; $300/month

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 1,001-5,000 employees