Senior Solutions Engineer

Crusoe

$155K — $200K *
Technical Services
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 2+ years in cloud infrastructure deployment, particularly in AI/ML, HPC, or GPU workloads
  • Proficiency with a major cloud platform (AWS, GCP, or Azure) for managing infrastructure
  • Experience deploying containerized applications using Kubernetes or Docker
  • Strong Linux command-line and scripting skills (Python or Bash)
  • Understanding of networking fundamentals including VPCs, subnets, load balancers, and DNS
  • Excellent technical communication, both written and verbal
  • Customer-facing skills with a focus on problem-solving and follow-up

Responsibilities

  • Deliver technical demonstrations and set up PoC environments for customer evaluation
  • Support technical discovery by mapping stakeholders and gathering requirements
  • Deploy and troubleshoot AI/ML workloads on Kubernetes, optimizing performance and costs
  • Assist customers in adapting workloads from major cloud platforms to Crusoe's infrastructure
  • Document product gaps for Engineering and relay structured feedback from customers
  • Ensure seamless post-sale transitions with comprehensive documentation

Benefits

  • Competitive compensation and equity packages
  • Restricted Stock Units for all employees
  • Generous paid time off and leave of absence programs
  • Comprehensive health, dental, and vision insurance
  • Employer contributions to Health Savings Accounts
  • Paid parental leave and life insurance
  • Short-term and long-term disability coverage
  • Professional development and tuition reimbursement opportunities
  • Mental health and wellness support
  • Commuter benefits including parking and transit allowances
  • Cell phone stipend
  • 401(k) retirement plan with company match
  • Volunteer time off
  • Global travel insurance and emergency assistance
  • Daily meals allowance
  • Location-specific perks and programs
Full Job Description
About the Role:

Crusoe Cloud is seeking a Solutions Engineer (early-to-mid career through senior level) to help enterprise customers deploy AI/ML workloads on Crusoe's high-performance GPU infrastructure. Based in our New York City office, you'll work alongside Account Executives and senior Solutions Engineers to run technical discovery, deliver demos and proofs of concept, and ensure customers land successfully on the platform. This is a hands-on role where you'll build environments, troubleshoot workloads, and grow toward owning the technical win end-to-end. This role is based full-time (Monday through Friday) in our New York City office.

What You'll Be Working On:
  • Deliver technical demos and stand up PoC environments for customers evaluating Crusoe Cloud, with clearly defined success criteria and timely execution
  • Support technical discovery alongside Account Executives, including mapping stakeholders, gathering requirements, and handling technical objections
  • Deploy and troubleshoot containerized AI/ML workloads on Kubernetes-based stacks, optimizing for performance and cost
  • Help customers adapt workloads from AWS, GCP, or Azure to Crusoe infrastructure, explaining tradeoffs along the way
  • Document product gaps and bugs from the field with the detail Engineering needs to reproduce them, and channel structured customer feedback to Product
  • Ensure clean post-sale handoffs by building transition docs and instance summaries so customer success teams start from a stable Day 1


What You'll Bring to the Team:
  • 2+ years of hands-on experience building, deploying, or operating cloud infrastructure, with exposure to AI/ML, HPC, or GPU workloads
  • Hands-on proficiency with at least one major cloud provider (AWS, GCP, or Azure), deploying and managing infrastructure rather than just consuming it
  • Experience deploying containerized workloads with Kubernetes or Docker
  • Strong Linux command-line skills and scripting ability in Python or Bash
  • Networking fundamentals: VPCs, subnets, load balancers, DNS, routing
  • Clear technical communication, comfortable presenting demos and writing documentation customers actually use
  • Customer-facing instincts: curiosity about business problems, composure under questions, and a bias toward follow-through


Bonus Points
  • Experience with distributed training or inference frameworks (PyTorch, Ray, Kubeflow)
  • Infrastructure-as-Code experience (Terraform, Ansible, CloudFormation)
  • GPU cluster, InfiniBand/RoCE, or Slurm exposure
  • Monitoring and observability tooling (Prometheus, Grafana, Datadog, CloudWatch)
  • Public technical content such as talks, blog posts, or how-to guides


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
  • Additional perks & programs specific to location


Compensation Range

Compensation will be paid in the range of up to $155,000 - $200,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data.

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