Senior Staff Solutions Engineer (NYC)

About the role

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.

Responsibilities

• Lead technical onboarding and deployment of complex AI/ML workloads with strategic enterprise customers—owning the POC through to post-sales optimization.
• 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.

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.

Qualifications

• 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).

Skills

• Strong technical background in AI/ML, Kubernetes, and cloud infrastructure.
• Excellent problem-solving and customer service skills.
• Ability to communicate effectively with both technical and non-technical stakeholders.

Benefits

• Competitive compensation and equity packages.
• Restricted Stock Units.
• Paid time off, paid holidays & leave of absence programs.
• Comprehensive health, dental & vision insurance.
• Employer contributions to HSA account.
• Paid parental leave.
• Paid life insurance, short-term and long-term disability.
• Professional development & tuition reimbursement.
• Mental health & wellness support.
• Commuter benefits (parking & transit).
• Cell phone stipend.
• 401(k) Retirement plan with company match up to 4% of salary.
• Volunteer time off.
• Global travel insurance & emergency assistance.
• Daily meals allowance.