Senior Staff Software Engineer, Knowledge Catalog For AI

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 2 years of experience with GenAI techniques (e.g., Large Language Models (LLMs), Multi-Modal, Large Vision Models) or with GenAI-related concepts (e.g., language modeling, computer vision).
• 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 Engineering, Computer Science, or a related technical field.
• 8 years of experience with data structures and algorithms.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
• 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.

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.

With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

Knowledge Catalog is the foundational context engine for the AI era designed as 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 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 context for both analytics and self-sustaining applications.

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.

Responsibilities:

• Generate critical ideas and own the architectural direction for highly ambiguous problem spaces. Maintain a direct approach to coding and system design while setting the standard for engineering excellence.
• Act as a technical multiplier. Navigate complex organizational structures to influence technical decisions and align outcomes across various Google Cloud products and distinct engineering organizations.
• Apply strong product-thinking to technical issues. Partner closely with engineering and product managers to define the long-term roadmap and ensure our technical capabilities align with customer and business needs.
• Provide technical guidance, mentorship, and leadership to engineers across the team, elevating the overall capability and velocity of the organization.