Software Engineering Manager II, Search

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.

In this role, you will solve the most critical issues in AI development today: sourcing and scaling high-quality training data. You will sit at the crucial upstream intersection of Google's flagship AI initiatives, and models that power Search, Bard, and the groundbreaking Gemini family. Your work will provide the fundamental ingredient for success by architecting and building the systems that make high-quality data accessible at an unprecedented scale.

In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

Responsibilities

• Set clear expectations with individuals based on their level and role and aligned to the broader organization's goals. Meet regularly with individuals to discuss performance and development and provide feedback and coaching.
• Review code developed by other engineers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Generate high-quality content for training Google's AI models.
• Build and optimize the systems and infrastructure required to make training data easily accessible and cost-effective at a large-scale.
Set the team's technical direction, make high-level architectural decisions, and own and drive large-scale, complex projects from conception to completion.