Software Engineering Manager II — Lead High-Throughput Systems

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

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Life insurance

Disability insurance

401(k) with company match

PTO 20 days per year

Sick time 40 hours/year

Maternity leave 28-30 weeks

Baby bonding leave 18 weeks

13 paid holidays

Job summary

Google is hiring a Software Engineering Manager to lead the Capacity Planning team within the GCS Resource Engineering group. You will oversee staffing, career growth, and the delivery of capacity planning solutions for high-throughput storage systems.

You will guide multiple teams across GCS, Networking, Compute and Data Center to align supply for AI workloads and scale the deployment of new capabilities globally.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 3 years of experience with large-scale infrastructure / distributed systems.
• 3 years in a technical leadership role.
• 2 years in people management / team leadership.

Responsibilities

• Manage team staffing, career growth, and uphold a high-performance bar.
• Own strategy and outcomes for capacity planning systems for high-throughput GCS products.
• Guide team through ambiguity by breaking down complex challenges into milestones.
• Navigate relationships across GCS, Networking, Compute, and Data Center teams.
• Drive engineering efforts to automate capacity adjudication and accelerate onboarding.

Skills

Software development

Distributed systems

Technical leadership

People management

Education

Bachelor's degree

Job description

Google is hiring a Software Engineering Manager to lead the Capacity Planning team within the GCS Resource Engineering group. You will oversee staffing, career growth, and the delivery of capacity planning solutions for high-throughput storage systems.

You will guide multiple teams across GCS, Networking, Compute and Data Center to align supply for AI workloads and scale the deployment of new capabilities globally.