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. Google operates the largest computing infrastructure in the world, where hardware investment and rapid innovation continuously accelerate. To power our global services for billions of users and external enterprise customers, our underlying modeling, simulation, and validation ecosystem must evolve to match this massive expansion. The Data Center Resource Modeling team is reenvisioning and rearchitecting the core software systems that simulate and validate our planetary-scale infrastructure. By building next-generation modeling platforms, we unlock unmatched efficiency, capacity optimization, and architectural decision-making for Google’s global data centers. The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide. We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits Learn more about benefits at Google. Responsibilities • Lead, manage, mentor, and grow a high-performing team of engineers dedicated to the DC Resource Modeling team. • Establish technology and product goal in collaboration with tech leads, partners, clients, and executive leadership. • Drive project planning, prioritization, and resource allocation to meet both the long term and short term goals. • Drive project reviews with executive leadership and stakeholders from partner organizations. • Oversee software logic governing physical data center racks throughout their operational lifecycle from planned deployments and commits to real-time, "as-maintained" active states. 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 in Infrastructure Systems, Hardware System Architecture, Data Analysis, Data Management, Data Center Architecture, Data Modeling, C++ or Java.