Cloud Solutions Architect (Pre-Sales) (AI)

TL;DR

Cloud Solutions Architect (Pre-Sales) (AI): Designing and optimizing AI-centric GPU cloud infrastructure for Fortune 500 companies and researchers with an accent on solution architecture, IaC, and GPU performance. Focus on conducting PoCs, optimizing ML pipeline scalability, and bridging technical requirements between clients and product teams.

Location: Remote (Must be based in the US)

Salary: $180,000 – $300,000

Company

Publicly traded company providing an AI-centric GPU cloud platform and infrastructure for training AI models.

What you will do

• Act as a technical advisor for clients, providing expertise throughout engagements.
• Conduct PoCs, workshops, and training sessions on GPU cloud technologies and best practices.
• Collaborate with clients to develop solution architectures based on business requirements.
• Design and document Infrastructure as Code (IaC) solutions and technical how-tos.
• Optimize customer pipeline performance and scalability.
• Support marketing efforts during hackathons, conferences, and webinars.

Requirements

• 5+ years of experience as a cloud solutions architect, system/network engineer, or developer.
• Hands-on experience with Terraform, Ansible, Kubernetes, and Python.
• Solid understanding of GPU computing (CUDA, OpenCL) for ML training and inference workloads.
• Deep knowledge of the cloud ML tools landscape from industry leaders.
• Legal authorization to work in the U.S. on a full-time basis without visa sponsorship.

Nice to have

• Experience thriving in fast-paced startup environments.
• Strong sense of ownership, accountability, and innovative problem-solving skills.
• Passion for democratizing access to AI infrastructure.

Culture & Benefits

• 100% company-paid medical, dental, and vision coverage for employees and families.
• 401(k) plan with a 4% match and stock options plan.
• Flexible remote work environment with mobile and internet stipends.
• Generous parental leave (20 weeks for primary caregivers, 12 weeks for secondary).
• Opportunity to work with cutting-edge AI technologies and one of the world's most powerful supercomputers.

Hiring process

• Virtual interview with the Talent Acquisition Lead for general fit.
• Virtual skills assessment with the Hiring Manager.
• Final round interview with C-level leadership.
• Post-interview reference and background checks.