Staff Software Engineer — AI Infrastructure & Data Center

Google LLC; Sunnyvale (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google LLC is hiring a Staff Software Engineer for Data Center and AI Infrastructure in Sunnyvale, CA. The role involves designing, building, and maintaining switch software powering Google’s data center and AI infrastructure, with focus on large-scale distributed systems and high performance networking.

The position emphasizes leadership, collaboration across teams, and contributing to AI-powered networking capabilities using TPUs and GPUs. In-person interviews are common.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience programming in C++.
• 5 years of experience testing, and launching software products.
• 5 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.
• Experience in problem management, problem-solving, network architecture, and network design.

Responsibilities

• Provide technical leadership on projects.
• Influence and coach a distributed team of engineers.
• Scale and performance tuning of a large-scale network.
• Design, develop, test, deploy, maintain and improve switch software.
• Work on projects enabling AI networking infrastructure, enabling high performing fabrics for Tensor Processing Units (TPUs) and GPUs.

Skills

C++ programming

Testing and releasing software

Large-scale infrastructure

Problem management

Network architecture

Education

Bachelor's degree

Job description

Google LLC is hiring a Staff Software Engineer for Data Center and AI Infrastructure in Sunnyvale, CA. The role involves designing, building, and maintaining switch software powering Google’s data center and AI infrastructure, with focus on large-scale distributed systems and high performance networking.

The position emphasizes leadership, collaboration across teams, and contributing to AI-powered networking capabilities using TPUs and GPUs. In-person interviews are common.