Software Engineer, Knowledge Catalog For AI

Google•Kirkland, WA

15h•$147,000 - $210,000

About The Position

Google software engineers develop technologies that help billions of users connect, explore, and interact with information. Engineers work on projects critical to Google's needs and may switch teams and projects as the business evolves. The role calls for versatility, leadership qualities, and enthusiasm for solving problems across the full stack. As part of the Knowledge Catalog team, you will help build a foundational context engine for the AI era: an always-on, enterprise-wide catalog that serves as a single source of truth for human users and AI agents. The work bridges raw data and business meaning, supporting Google's Agentic Data Cloud and enabling AI agents to reason, act, and execute on complex enterprise data. Knowledge Catalog helps data teams and AI developers discover data, enforce policies, and retrieve rich context for analytics and autonomous applications. You will empower AI agents across Google Cloud and third-party data ecosystems, including BigQuery, lakehouses, and operational databases.

Requirements

Bachelor's degree or equivalent practical experience.
At least 2 years of experience developing large-scale infrastructure, distributed systems, or networks, or experience with compute technologies or storage.
At least 2 years of software development experience, or 1 year of software development experience in an industry setting with an advanced degree.
Experience with Artificial Intelligence, Generative AI, and Generative AI Agents.
Experience with distributed systems and software architecture.

Nice To Haves

Master's degree or PhD in Computer Science or a related technical field.
Experience developing Cloud or SaaS products.
Experience shipping 0-to-1 AI applications, with a holistic understanding of product, quality, and infrastructure.
Knowledge of data warehouses, big data, SQL, and data governance.

Responsibilities

Write product or system development code.
Participate in or lead design reviews with peers and stakeholders to decide among available technologies.
Review code developed by other developers and provide feedback to ensure best practices, including style guidelines, code check-in, accuracy, testability, and efficiency.
Contribute to existing documentation or educational content and adapt it based on product or program updates and user feedback.
Triage product or system issues and debug, track, and resolve them by analyzing the sources of issues and their impact on hardware, network, or service operations and quality.