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.
Knowledge Catalog is the foundational context engine for the AI era. Designed as an always-on enterprise-wide catalog for AI, it serves as the single source of truth for both human users and AI agents. By bridging the gap between raw data and true business meaning, we power Google's Agentic Data Cloud (demoed at Google Cloud Next ’26 - Agentic Data Cloud), enabling AI agents to reason, act, and execute on complex enterprise data. It provides universal business context and governance for your entire data estate. Data teams and AI developers use Knowledge Catalog to discover data, enforce policies, and retrieve rich context for both analytics and autonomous applications.
In this role, you will empower AI agents across industry-leading Google Cloud and third-party data ecosystems (BigQuery, lakehouses, operational databases, etc.).
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.
The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about
benefits at Google.
Responsibilities
- Drive technical projects and provide contributions.
- Design and implement features/components to support agentic workflows, catalog infrastructure, metadata enrichment, etc.
- Perform rapid prototyping and experimentation and take ideas from concept to production.
- Coordinate and drive improvements in Knowledge Catalog engineering and operational excellence.
- Work effectively across boundaries in a distributed team setup to deliver on organizational goals, and work with customers to help find solutions to their blocking issues.
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, storage or hardware architecture.
- 1 year of experience with applied AI/ML and common GenAI technologies.
- Experience with software development in one or more general purpose programming languages (e.g., Java, C/C++, or Go, etc.).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- Experience developing Cloud or SaaS products.
- Experience with shipping 0-to-1 AI applications, with a holistic understanding of product, quality, and infra.
- Knowledge of data warehouses, big data, SQL, and data governance.