Senior Solutions Engineer: AI Infra, Kubernetes & MLOps

Crusoe Energy Systems LLC; New York (NY); On-site; USD 175,000 - 250,000; Full time

Benefits offered by this job

Competitive compensation and equity packages

Comprehensive health, dental & vision insurance

Paid parental leave

401(k) Retirement plan with company match

Professional development & tuition reimbursement

Global travel insurance & emergency assistance

Job summary

Crusoe Energy Systems LLC is seeking a Senior Solutions Engineer in New York to work with strategic enterprise customers to deploy AI/ML workloads on high-performance GPU infrastructure. This hands-on role emphasizes deep technical expertise in Kubernetes and MLOps.

Responsibilities include leading customer onboarding, optimizing workloads post-sale, and providing technical leadership. Ideal candidates have over 7 years of experience and are passionate about AI infrastructure.

Qualifications

• 7+ years building and deploying containerized workloads.
• Experience deploying ML frameworks like Ray and MLflow on Kubernetes.
• Familiarity with compute, storage, and networking in cloud environments.
• Strong communication skills and collaborative mindset.

Responsibilities

• Lead technical onboarding and deployment of AI/ML workloads.
• Architect and deploy ML workloads using Kubernetes.
• Deploy and optimize workloads directly on Crusoe infrastructure.
• Help customers migrate workloads across AWS, Azure, GCP.
• Conduct workshops, demos, and solution reviews.
• Provide feedback to engineering and product teams.

Skills

Kubernetes expertise

MLOps deployment experience

Cloud infrastructure knowledge

Customer-facing confidence

Linux and CLI proficiency

Collaborative energy

Tools

Helm

Terraform

Docker

Job description

Crusoe Energy Systems LLC is seeking a Senior Solutions Engineer in New York to work with strategic enterprise customers to deploy AI/ML workloads on high-performance GPU infrastructure. This hands-on role emphasizes deep technical expertise in Kubernetes and MLOps.

Responsibilities include leading customer onboarding, optimizing workloads post-sale, and providing technical leadership. Ideal candidates have over 7 years of experience and are passionate about AI infrastructure.