Senior Staff Software Engineer, Google Cloud Compute, Performance
Google
Seattle, WA, US
Onsite
$262k–$365k · announced
2026-06-18
What this role pays in Seattle
$107K - $192K
Low
$107K
Median
$149K
High
$192K
Official salary benchmark · BLS OEWS 2025
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Job description
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
* Health, dental, vision, life, disability insurance
* Retirement Benefits: 401(k) with company match
* Paid Time Off: 20 days of vacation per year, accruing at a rate of 6\.15 hours per pay period for the first five years of employment
* Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
* Maternity Leave (Short\-Term Disability \+ Baby Bonding): 28\-30 weeks
* Baby Bonding Leave: 18 weeks
* Holidays: 13 paid days per year
### **Minimum qualifications:**
* Bachelor's degree or equivalent practical experience.
* 8 years of experience programming in C\+\+.
* 7 years of experience building and developing large\-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware.
* Experience in one or more of the following domains: OS kernels, hypervisors/virtualization stacks (e.g., KVM, Xen), high\-performance networking drivers, storage stacks.
* Experience with CPU/memory architectures (e.g., x86, ARM) and modern server hardware performance characteristics.
* Experience as an architect or technical lead for multi\-year infrastructure initiatives from conception to global deployment.
### **Preferred qualifications:**
* Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
* 8 years of experience with data structures/algorithms.
* 5 years of experience in a technical leadership role leading project teams and setting technical direction.
* Experience collaborating directly with principal engineers at strategic enterprise client organizations to root\-cause and resolve complex, large\-scale system performance bottlenecks.
* Understanding of hardware/software boundaries, including performance profiling tools, microarchitectural optimi