Principal Engineer, Shopping Product Graph Data Infrastructure

Minimum qualifications:

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
• 15 years of experience in software engineering.
• Experience leading the architecture and design of distributed systems and data infrastructures.
• Experience providing technical leadership, setting technical direction, and driving consensus across multi-disciplinary engineering organizations.
• Experience with machine learning infrastructure, AI integration, or large language model (LLM) applications in production environments.

Preferred qualifications:

• Master's degree or PhD in Computer Science, Artificial Intelligence, or a related field.
• Experience successfully driving fundamental architectural transformations for legacy, high-traffic data ecosystems.
• Domain expertise in e-commerce, product knowledge graphs, search ranking, or commercial platforms.
• Ability to navigate complex organizational structures, seamlessly translating advanced research into tangible, real-world product impact.

About the job:

The Shopping Graph is Google's comprehensive, interconnected dataset of commercial information, designed to power various shopping experiences across Google services, including Search, Ads, YouTube, Discover, Chrome, and the Gemini App. The Shopping Product Graph is a key subset focused on modeling billions of purchasable products, their complex relationships, and their visual, subjective, and specification-based attributes. By synthesizing information from web crawls, merchant catalogs, and manufacturer inputs, we own the discovery, creation, and linking of all entities to form a shared, highly accurate, and complete commercial model that empowers millions of merchants and billions of users globally.

As a Principal Engineer for the Shopping Product Graph Data Infrastructure, you will drive the architectural evolution of Google's global commerce data ecosystem. You will dictate the long-term data infrastructure strategy, architecting systems capable of managing billions of entities while maintaining exceptional resilience and scale in the agentic commerce era. You will operate at the intersection of advanced machine learning and large-scale distributed systems, driving a step-function change in capability, quality, and execution velocity. You will ensure our product modeling and understanding seamlessly power new AI-driven capabilities in Search, Ads, and YouTube. Your technical leadership will impact thousands of engineers, billions of users, and a core pillar of Google's business generation. As a Principal Engineer, you will not only design industry-leading systems but also cultivate an engineering culture of excellence, mentoring senior technical leaders and setting the standard for data-driven product innovation.

People shop on Google more than a billion times a day - and the Commerce team is responsible for building the experiences that serve these users. The mission for Google Commerce is to be an essential part of the shopping journey for consumers - from inspiration to to a simple and secure checkout experience - and the best place for retailers/merchants to connect with consumers. We support and partner with the commerce ecosystem, from large retailers to small local merchants, to give them the tools, technology and scale to thrive in today’s digital world.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $307000 - $427000 (USD) + 30% bonus target + equity + benefits

Learn more about benefits at Google. Responsibilities:

• Architect the end-to-end technical strategy for the next generation of the Shopping Product Graph data infrastructure, building resilient, planetary-scale systems that power Google's commercial AI experiences.

• Partner closely with executive stakeholders, engineering directors, and product leadership across Search, Ads, and YouTube to align advanced infrastructural capabilities with broad, multi-year strategic business objectives.

• Advocate for the integration of LLM inference and large-scale clustering techniques into the core data infrastructure, bridging advanced research with massive-scale consumer applications.

• Establish industry-leading standards for data-driven product quality, pioneering advanced experimentation and LLM-based evaluation frameworks to accelerate engineering iteration and model accuracy.

• Serve as a cornerstone of technical excellence, actively guiding, mentoring, and elevating a large organization of Senior Staff and Staff Engineers to solve Google's ambiguous and complex commerce challenges.