Software Engineer Manager II, Front End, AI Developer Tools Product Integrations

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.

The Developer Intelligence group within Google Cloud AI Developer Tools (AIDT) puts AI and model intelligence into every Google Cloud Platform developer workflow. We are the engineering organization responsible for the complete developer journey on Gemini Enterprise—delivering high-polish product integrations, secure cloud agent runtimes, and repository-fixing engines.

The Product Integrations pillar builds all the touchpoints where software engineers, platform developers, and cloud administrators interact with Gemini Enterprise. Our scope spans multi-IDE extensions (VS Code, Visual Studio, Eclipse, plus JetBrains, Zed, and Xcode via the Agent Client Protocol), the Google Cloud Pantheon Admin Web Console, developer terminal workflows (Gemini CLI), and partner engineering operations.

The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.

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.

• Mentor a New York based team of engineers, fostering a psychologically safe culture centered on continuous feedback and technical excellence.
• Partner with Product Managers, User Experience (UX), and Developer Relations (DevRel) to advance the developer experience, including inline completions and agentic refactoring.
  
• Oversee technical architecture across VS Code, IntelliJ, LSP, and Pantheon, prioritizing User Interface (UI) responsiveness, low resource footprint, and enterprise-grade security.
  
• Collaborate with dedicated Technical Leads and manage external partner teams to maintain core surfaces like Gemini Code Assist.
  
• Partner with peer pillars, Vertex AI, DeepMind, and Core Developer Infrastructure to deliver cohesive flagship innovations.
  

Minimum qualifications:

• Bachelor’s degree, or equivalent practical experience.
  
• 8 years of experience in software development.
  
• 3 years of experience with front-end and user interface development.
• 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 shipping developer tools or IDE extensions (e.g., VS Code) with a strong intuition for developer experience and productivity workflows.
• Experience integrating Large Language Models (LLMs) into interactive client applications, including streaming tokens and context management.
• Experience managing hybrid engineering teams, including full-time SWEs and vendor partners.