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Crusoe Logo Crusoe · IT - Software Development

Senior+ Solutions Engineer

Ireland, Dublin · Job Posted February 21, 2026
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Job Description

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.

Job Responsibility

  • 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

Requirements

  • 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
  • Must be able to pass a background check
  • Embody the Company values

Nice to have

  • 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)

What we offer

  • pension contributions
  • private health and dental insurance
  • income protection
  • life assurance
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