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Salary: USD 155,000 - 200,000 / annual
Crusoe is a vertically integrated AI infrastructure company that owns and operates the full stack from energy generation to AI workloads. The company is solving the power bottleneck constraining AI compute availability through an energy-first approach.
As a Senior Solutions Engineer, you'll be based in the New York City office and work with enterprise customers to deploy AI/ML workloads on Crusoe's high-performance GPU infrastructure. You'll partner with Account Executives and other Solutions Engineers to drive technical discovery, deliver product demonstrations, build proof-of-concept environments, and ensure successful customer onboarding.
Key responsibilities include: delivering technical demos and standing up PoC environments with defined success criteria; supporting technical discovery by mapping stakeholders and gathering requirements; deploying and troubleshooting containerized AI/ML workloads on Kubernetes-based infrastructure; helping customers migrate workloads from AWS, GCP, or Azure to Crusoe while explaining tradeoffs; documenting product gaps and bugs with sufficient detail for Engineering reproduction; and ensuring smooth post-sale handoffs through comprehensive transition documentation.
You'll need 2+ years of hands-on cloud infrastructure experience with exposure to AI/ML, HPC, or GPU workloads. Required skills include proficiency with at least one major cloud provider (AWS, GCP, Azure) at the infrastructure deployment level, containerized workload deployment using Kubernetes or Docker, strong Linux command-line and Python/Bash scripting abilities, and networking fundamentals (VPCs, subnets, load balancers, DNS, routing). You should be a clear technical communicator comfortable presenting demos and writing customer-facing documentation, with genuine curiosity about business problems and strong follow-through instincts.
Bonus qualifications include experience with distributed training/inference frameworks (PyTorch, Ray, Kubeflow), Infrastructure-as-Code tools (Terraform, Ansible, CloudFormation), GPU clusters or InfiniBand/RoCE, monitoring tools (Prometheus, Grafana, Datadog), and public technical content creation.
