Senior Software Engineering Manager, GCE… at Google · Kirkland

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 architecture.
• 5 years of experience in a technical leadership role.
• 5 years of experience in a people management or team leadership role.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• Experience managing managers and scaling large, high-performing engineering organizations through periods of growth or technical transformation.
• Deep domain expertise in reliability engineering, automated disaster recovery, or cloud security and compliance within regulated environments.
• Proven ability to demonstrate staff-level technical judgment and decision-making for large-scale back-end systems and complex platform architectures.
• Exceptional cross-functional collaboration and communication skills, with a track record of partnering with product, operations, and executive stakeholders to drive platform strategy.

About the job

Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.

With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.

In this role, you will lead the shift to cellular architectures and multi-dimensional sharding to contain deployment blast radius and prevent multi-regional failures. You will shift telemetry to customer-perceived sensitivity, using AI-driven anomaly detection and automated rollbacks to neutralize failures early, and will modernize resource conservation by transitioning to dynamic throttling and adaptive quotas for AI workloads. You will establish continuous, automated validation pipelines to ensure data stores meet strict Recovery Point Objective/Recovery Time Objective (RPO/RTO) objectives and maintain resiliency.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Scale high-performing engineering teams to manage the foundational infrastructure of the GCE Control Plane Platform.
• Build a "Reliable by Design" environment, establishing GCE as the industry gold standard for resiliency against hyper-accelerated AI workloads.
• Foster an engineering culture focused on blast radius containment, hitless maintenance, and dynamic capacity assurance.
• Guide multi-dimensional sharding and automated disaster recovery for a rapidly scaling AI fleet.
• Define the technical goal and lead initiatives to enhance platform security and automate continuous compliance.