Staff Cloud Compute Performance Architect

Google; Seattle (WA); On-site; USD 207,000 - 300,000; Full time

Benefits offered by this job

20% bonus target

Equity

Benefits

Job summary

Google’s staff software engineers in the Google Cloud Compute (GCE) Performance team drive the next-generation VM offerings and push the boundaries of hardware efficiency and scalable software architecture. You will lead cross-functional initiatives, mentor engineers, and partner with strategic customers to optimize performance across massive-scale workloads.

We value leadership, deep system knowledge, and the ability to align engineering direction with product goals while managing complex

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience programming in C++.
• 5 years building large-scale infrastructure, distributed systems, or related compute/storage/hardware areas.
• Experience with CPU/memory architectures (e.g., x86, ARM) and modern server hardware.
• Experience as architect or technical lead for multi-year infrastructure initiatives.

Responsibilities

• Define roadmap for GCE’s next-generation VM offerings, translating goals into execution plans.
• Design and develop scalable solutions to optimize VM performance and hardware efficiency.
• Lead cross-functional initiatives across hardware, kernel, virtualization, and product teams.
• Act as technical advisor to critical customers, analyze and optimize massive-scale workloads.
• Mentor engineers, conduct design reviews, and establish engineering practices for performance.

Skills

C++ programming

Large-scale infrastructure

OS kernels & virtualization

CPU/Memory architectures

Technical leadership

Education

Bachelor's degree or equivalent

Master’s or PhD in Engineering/CS

Job description

Google’s staff software engineers in the Google Cloud Compute (GCE) Performance team drive the next-generation VM offerings and push the boundaries of hardware efficiency and scalable software architecture. You will lead cross-functional initiatives, mentor engineers, and partner with strategic customers to optimize performance across massive-scale workloads.

We value leadership, deep system knowledge, and the ability to align engineering direction with product goals while managing complex