GPU Data Center Architect — AI-Driven Infra Solutions

Nscale; New York, San Francisco, Seattle (NY, CA, WA); On-site; USD 160,000 - 290,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Flexible PTO

Parental leave

Retirement plan

Job summary

Nscale is seeking a Data Center Solutions Architect to design and deliver end-to-end GPU infrastructure solutions across networking, compute, storage and data center systems in the United States. You will translate customer needs into detailed architectures and specifications, and collaborate with internal teams to ensure feasible, scalable deployments.

The role requires strong data center experience, expertise in leaf/spine networking, and familiarity with AI/ML workloads.

Qualifications

• Strong experience designing large-scale data center solutions.
• Ability to translate complex requirements into architectures.
• Excellent communication with diverse audiences.

Responsibilities

• Engage directly with customers to understand technical requirements and workloads.
• Design full-stack data center solutions including GPU racks, storage, and data pipelines.
• Define control plane and management systems for deployment.
• Translate customer needs into detailed architectures and specs.
• Collaborate with engineering teams to ensure feasibility and alignment.
• Support deployment planning and ensure performance and reliability targets.
• Act as a trusted technical advisor to customers.
• Stay up-to-date with AI tooling to augment design processes.

Skills

Data center arch

Networking leaf/spine

GPU systems

AI/ML workloads

Storage systems

Communication

Customer-facing

Job description

Nscale is seeking a Data Center Solutions Architect to design and deliver end-to-end GPU infrastructure solutions across networking, compute, storage and data center systems in the United States. You will translate customer needs into detailed architectures and specifications, and collaborate with internal teams to ensure feasible, scalable deployments.

The role requires strong data center experience, expertise in leaf/spine networking, and familiarity with AI/ML workloads.