Senior Customer Engineer — AI Infrastructure & HPC

Google; Washington (District of Columbia); Hybrid; USD 152,000 - 221,000; Full time

Job summary

Google Cloud is seeking a Customer Engineer to partner with technical Sales teams, translating customer needs into scalable AI/ML infrastructure solutions. You will lead technical discussions with customer architects and executives, troubleshoot challenges, and drive proofs of concepts and demonstrations.

As a trusted advisor, you will propose GPU/TPU hardware, ML frameworks, and data analytics approaches, coordinating across product, engineering, and services to deliver value.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 10 years of cloud native architecture experience in customer-facing or support roles.
• Experience engaging with technical stakeholders or executive leaders.
• Experience with ML model development and deployment.
• Active TS/SCI security clearance with polygraph; US travel up to 20%.

Responsibilities

• Partner with Sales teams to differentiate Google Cloud to customers.
• Serve as the primary technical partner and trusted advisor for customers.
• Troubleshoot questions, run proofs of concepts and demos.
• Architect cross-pillar cloud solutions to solve business issues.
• Deliver technical win and define delivery and consumption plans.

Skills

Cloud architecture experience

Executive presentation

ML model development

Security clearance TS/SCI with poly

Business travel up to 20%

Education

Bachelor's degree or equivalent practical experience

Tools

Keras

PyTorch

TensorFlow

JAX

Slurm

vLLM

Ray

Kubernetes (K8s)

Job description

Google Cloud is seeking a Customer Engineer to partner with technical Sales teams, translating customer needs into scalable AI/ML infrastructure solutions. You will lead technical discussions with customer architects and executives, troubleshoot challenges, and drive proofs of concepts and demonstrations.

As a trusted advisor, you will propose GPU/TPU hardware, ML frameworks, and data analytics approaches, coordinating across product, engineering, and services to deliver value.