Senior AI Infrastructure Field Solutions Architect

Google LLC; New York (NY); On-site; USD 233,000 - 324,000; Full time

Benefits offered by this job

Health, dental, vision, life, and 장애

401(k) with company match

Paid Time Off: 20 days per year, 6.15h

Sick Time: 40 hours/year (69 Seattle)

Maternity Leave 28–30 weeks

Baby Bonding Leave 18 weeks

Holidays 13 days

Job summary

Google Cloud is seeking an AI Infrastructure Field Solution Architect to support commercial teams in piloting and deploying TPU and GPU hardware for enterprises and startups, enabling faster innovation.

You will guide discussions on network topology, fabric architecture, and compute/storage integration, including on-site client visits and cost-to-performance tradeoffs, shaping platform roadmaps with internal teams.

Qualifications

• Bachelor's degree in STEM or equivalent practical experience.
• 10 years of experience with data center technologies and deployments.
• Experience with data center networking: routing, switching, DNS, IP addressing; compute/storage concepts; power and cooling.
• Experience with AI model training/inference and OSS frameworks such as PyTorch, JAX, etc., and optimizing performance vs. costs.
• Scripting in Python, YAML, and Kubernetes.

Responsibilities

• Learn more about benefits at Google .
• Advise customers on AI accelerators integration into business strategy by designing training and inferencing platforms and incorporating customers' data center technologies.
• Demonstrate Google Cloud accelerators, profiling, benchmarking, and model performance optimization.

Skills

Data center networking concepts

Python scripting

YAML

Kubernetes

Education

Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience

Tools

PyTorch

JAX

YAML

Kubernetes

Job description

Google Cloud is seeking an AI Infrastructure Field Solution Architect to support commercial teams in piloting and deploying TPU and GPU hardware for enterprises and startups, enabling faster innovation.

You will guide discussions on network topology, fabric architecture, and compute/storage integration, including on-site client visits and cost-to-performance tradeoffs, shaping platform roadmaps with internal teams.