Job Description
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
- 3 years of experience in a technical leadership role, overseeing projects, with 2 years of experience in a people management, supervision or team leadership role.
Preferred qualifications:
- Experience with Android, device communication technologies such as Matter or mobile app development (Java/Kotlin) in the context of device ecosystems.
Experience with LLM application development, RAG, and integrating AI Agent frameworks (e.g., Claude Code, Google Antigravity, Codex) to drive workflow automation.
- Proven experience in leading software engineering teams and establishing engineering best practices within a complex hardware/software matrix organization.
- Practical experience in software testing (unit testing, integration test design) and CI/CD pipeline automation for cross-platform systems.
Experience with LLM application development, RAG, and integrating AI Agent frameworks (e.g., Claude Code, Google Antigravity, Codex) to drive workflow automation.
Experience with LLM application development, RAG, and integrating AI Agent frameworks (e.g., Claude Code, Google Antigravity, Codex) to drive workflow automation.
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.
The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.
Responsibilities
Drive cross-functional technical coordination across Google Home app, backend and device teams, and manage a team of 10+ engineers building infrastructure for the helpful home.
Build AI tools to optimize engineer workflows (e.g., AI-generated code, automated test generation) and create AI agents to automatically triage bugs and perform Root Cause Analysis (RCA) for complex device-to-app interactions.
Act as the primary visionary for what an AI-ready codebase looks like for Google Home. Define the technical requirements for instrumentation, logging enhancements, and monitoring that enable AI agents to thrive.
Define and implement novel validation strategies and evaluation frameworks (e.g., LLM-based Evals) for agentic features and non-deterministic AI behaviors that cannot be validated through traditional testing methodologies.
Drive cross-functional technical coordination across Google Home app, backend and device teams, and manage a team of 10+ engineers building infrastructure for the helpful home.
Build AI tools to optimize engineer workflows (e.g., AI-generated code, automated test generation) and create AI agents to automatically triage bugs and perform Root Cause Analysis (RCA) for complex device-to-app interactions.
Act as the primary visionary for what an AI-ready codebase looks like for Google Home. Define the technical requirements for instrumentation, logging enhancements, and monitoring that enable AI agents to thrive.
Define and implement novel validation strategies and evaluation frameworks (e.g., LLM-based Evals) for agentic features and non-deterministic AI behaviors that cannot be validated through traditional testing methodologies.