Software Engineering Manager, Data Center Fleet Health

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; overseeing projects.
• 2 years of experience in a people management, supervision/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 data center technology and how data centers operate and run.

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.

Join the Fleet Detection and Analytics team to take control of one of the largest data center footprints in the world. Be directly responsible for delivering reliable capacity for use by all Google products and cloud customers. Automate the detection of failures in the data center. We find innovative ways to increase up-time reduce parts costs reduce risk and more efficiently operate the life-cycle of our hardware. We are delivering cost savings while enabling new hardware every month. We are a key component in making Cloud cheap and reliable for Google's internal and external customers.

The ML, Systems, & 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.

Responsibilities

• Lead a distributed team that builds the core monitoring infrastructure for Google's data center infrastructure.
• Contribute to the reliability of our existing ML and Cloud infrastructure as well as the next generation infrastructure that will support ML/Cloud.
• Define the multi-year roadmap for the team.