Engineering Manager, Capacity Management, Google Fleet

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 build service and resource capacity management that is simple, trustworthy, and efficient. You will lead a critical set of products that enable automated management of all resource types, at multiple location levels. Your goal is to increase overall resource obtainability and reduce safety stock while concurrently increasing inventory efficiency through intelligent automation. You will be responsible for scoping, shaping, and delivering a future where capacity supply and provisioning remove the need for human intervention.

The ML, Systems, and Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

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

US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Lead the design and implementation of a resource distribution ecosystem. You will turn a big-picture plan into concrete projects for yourself and the team.
• Lead the transition to artifact-driven software development, ensuring that user intent is captured as structured artifacts to guide autonomous agents.
• Take on issues at the intersection of large-scale distributed systems, risk modeling, and policy enforcement. This includes designing universal, high-level resource abstractions that operate above the level of a single data center.
• Collaborate with partner teams across all Product Areas to define requirements and deliver a unified platform.
• Coach and grow engineers on the team, build a strong leadership bench, while fostering a culture of technical excellence, thinking, and innovation.

Minimum qualifications:

• Bachelor’s degree, or equivalent practical experience.
  
• 8 years of experience in software development.
  
• 3 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
• 3 years of experience in a technical leadership role.
• 2 years of experience in a people management or team leadership role.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
  
• 3 years of experience working in a complex, matrixed organization.
  
• Experience with resource management, capacity management, or SQL pipelines.