Senior Solutions Engineer
Crusoe is an AI infrastructure and cloud computing company. It provides GPU cloud capacity, managed AI services, inference, fine-tuning, data centers, and energy infrastructure for AI developers and enterprise customers.
Maintainer signals as of 8/23/2026
Funding history
Projects
About Crusoe, Inc
Crusoe designs, builds, and operates energy-first AI infrastructure, including data centers, GPU cloud computing, and modular AI factories. Crusoe Cloud provides GPU clusters, managed Kubernetes and Slurm, storage, networking, observability, managed inference, serverless fine-tuning, and model deployment through Crusoe Intelligence Foundry. Its customers include AI startups, enterprises, and organizations developing training, inference, analytics, and other compute-intensive workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Lead technical onboarding, proofs of concept, and deployment of AI and machine learning workloads for enterprise customers. Architect Kubernetes and MLOps infrastructure, optimize workloads, translate deployments across cloud platforms, conduct technical workshops and demos, document solutions, and relay customer feedback to engineering and product teams.
Requirements
- 2+ years of hands-on experience building, deploying, or operating cloud infrastructure
- Exposure to AI/ML, HPC, or GPU workloads
- Hands-on proficiency with AWS, GCP, or Azure
- Experience deploying containerized workloads with Kubernetes or Docker
- Strong Linux command-line skills
- Scripting ability in Python or Bash
- Knowledge of VPCs, subnets, load balancers, DNS, and routing
- Clear technical communication and presentation skills
- Ability to gather customer requirements and handle technical questions
- Experience with PyTorch, Ray, or Kubeflow is a bonus
- Infrastructure-as-Code experience with Terraform, Ansible, or CloudFormation is a bonus
- GPU cluster, InfiniBand, RoCE, or Slurm exposure is a bonus
- Experience with Prometheus, Grafana, Datadog, or CloudWatch is a bonus
Responsibilities
- Deliver technical demos
- Stand up proof-of-concept environments
- Support technical discovery with Account Executives
- Map stakeholders and gather requirements
- Handle technical objections
- Deploy and troubleshoot containerized AI and machine learning workloads
- Optimize workloads for performance and cost
- Help customers adapt workloads from AWS, GCP, or Azure
- Document product gaps and bugs
- Channel structured customer feedback to Product
- Build transition documents and instance summaries for post-sale handoffs
Benefits
- Restricted Stock Units
- Paid time off
- Paid holidays
- Leave of absence programs
- Comprehensive health insurance
- Dental insurance
- Vision insurance
- Employer contributions to HSA account
- Paid parental leave
- Paid life insurance
- Short-term disability insurance
- Long-term disability insurance
- Professional development
- Tuition reimbursement
- Mental health support
- Wellness support
- Commuter benefits for parking and 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
- Additional location-specific perks and programs
