Software Engineering Manager, Agentic AI

Minimum qualifications:

• Bachelor’s degree, or equivalent practical experience.
  
• 8 years of experience in software development.
  
• 3 years of experience in a technical leadership role.
• 2 years of experience in a people management or team leadership role.
• Experience with distributed systems.

Preferred qualifications:

• Master's degree or PhD in Computer Science, or a related technical field.
• 3 years of experience working in a complex, matrixed organization.
  
• Experience with data center management.
• Experience with Generative AI.

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.

The Cluster Planning team develops software to optimize the design, planning, deployment, and decommissioning of cluster layouts for Google data centers. Our fleet consumes as much power as the entire city of San Francisco, so we're handling a number of fun, open-ended, and challenging problems to optimize rack placement, reduce our environmental impact, and save Google money.

We will drive the roadmap to design and launch Agentic AI Applications to efficiently deploy these resources in the optimal configuration for our customers across various product areas at Alphabet and for all our external customers supported by Google Cloud.

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.

The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

We will drive the roadmap to design and launch Agentic AI Applications to efficiently deploy these resources in the optimal configuration for our customers across various product areas at Alphabet and for all our external customers supported by Google Cloud.

Responsibilities

• Propose, design, and develop new functionality to create a robust automation system for Google's supply chain and data center deployments.
• Ensure our production-facing Service Level Objectives (SLOs) are met while continuously adding new capabilities to our software.
  
• Influence, review, and represent our team across leadership forums.
  
• Leverage Agentic AI to improve automation and reduce turnaround times.
• Lead and drive long-term software architecture and roadmaps to build and deploy Agentic AI applications to manage rack deployments of GPUs, TPUs, and networking racks.