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.
• 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.
• Experience architecting and developing software or infrastructure for scalable, distributed systems.

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.

Responsibilities

• Lead the design, implementation, and optimization of high-scale persistence layers and metadata engines that serve as the "Source of Truth" for millions of devices.
• Partner with orchestration and intelligence teams to architect storage solutions for advanced AI features.
• Enhance metadata structures and eliminate data fragmentation to unlock seamless integration with
  Large Language Models (LLMs) and improve the reliability of device-facing services.
• Provide technical guidance to engineers, fostering a culture of high performance, rigorous incident management, and methodical architectural design.