Software Engineer, Looker Developer Infrastructure and Tooling

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

The Looker Developer Infrastructure & Tooling team is dedicated to maximizing the efficiency, quality, and velocity of the Looker engineering organization. We build and maintain the core infrastructure, CI/CD pipelines, and advanced tooling powering the entire Software Development Life Cycle for Looker. As we scale, our team is leading the transition to Agentic Development, where human developers delegate mechanical tasks to AI-powered agents. We are inventing next-generation Dev AI capabilities, embedding code assistants and agentic debugging frameworks directly into local developer environments and pipeline automation. In this role, you will take ownership of developing and optimizing internal tools, test frameworks, and build pipelines, with an increasing emphasis on Dev AI integrations. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $147000 - $211000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google . Responsibilities

Write product or system development code.

Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.

Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).

Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.

Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.

Qualifications

• Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.

• 2 years of experience with software development or 1 year of experience with an advanced degree in an industry setting.

• 2 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies or storage.

• Experience with databases, monitoring, and logging.

Preferred qualifications

• Master's degree or PhD in Computer Science or related technical fields.

• Experience with build automation tools and dependency management systems like Bazel or Nix.

• Experience administering or utilizing testing platforms for highly complex, Monolith/Enterprise setups.

• Experience embedding Large Language Models (LLMs) into internal Developer Experience (DevEx) or inner-loop diagnostics/debugging platforms.

• Experience in agentic development and ability to build, prototype, or integrate autonomous AI agents (using frameworks like ADK, Orcas, or Agency) or fine-tune Model Context Protocols (MCP).

• Familiarity with Cloud Infrastructure and modern deployment frameworks (Louhi, Prow, or equivalent).