Senior Staff Software Engineer, Knowledge Catalog For AI

About the role

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.

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

experience, and relevant education or training.

US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits

Learn more about benefits at Google

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

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.