Software Engineer III, Knowledge Catalog For AI

About the role

MINIMUM QUALIFICATIONS:

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with developing large-scale infrastructure, distributed

systems or networks, or experience with compute technologies or storage.

• 2 years of experience with software development or 1 year of experience with

an advanced degree in an industry setting.

• 1 years of experience with applied AI/ML or GenAI technologies.
• Experience with software development in one or more general purpose

programming languages (e.g., Java, C/C++, or Go, etc.).

• Experience with Distributed Systems.

PREFERRED QUALIFICATIONS:

• Master's degree or PhD in Computer Science or related technical fields.
• Experience with shipping 0-to-1 AI applications, with a holistic

understanding of product, quality, and infra.

• Experience developing Cloud or SaaS products.
• Knowledge of data warehouses, big data, SQL, and data governance.

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.

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 reliable

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 analytics and autonomous applications.

In this role, you'll empower AI agents across industry-leading Google Cloud and

third-party data ecosystems, including 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.

Individual pay is determined by factors including job-related skills,

experience, and relevant education or training.

US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

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.