Join Google's innovative search team to shape the future of information discovery. As a Staff Software Engineer, you'll be instrumental in developing next-generation technologies that impact billions of users globally. This role focuses on advancing Search's AI Developer Tools Platform, contributing to massive-scale systems, and driving AI-native engineering practices.

This is an opportunity to work on critical projects that redefine how people find and interact with information. You will leverage your technical expertise to manage priorities, design robust solutions, and contribute to a universally accessible and useful search experience.

Advance your career by solving complex engineering challenges and expanding our infrastructure. Your contributions will directly impact the scalability, reliability, and performance of Google Search, enabling 10x AI-driven development velocity.

Architect and evolve the core components of Search's AI Developer Tools Platform, including evaluation infrastructure and high-fidelity queryset pipelines.

Provide strong technical leadership for high-impact projects, guiding teams toward innovative solutions.

Lead the integration of autonomous agentic workflows into the Search software and prompt development lifecycle, championing AI-native engineering principles.

Influence and mentor a distributed team of engineers, fostering a collaborative and high-performing environment.

Drive cross-team technical strategy as a thought leader, aligning platform evolution with broader Search AI architecture and collaborating with diverse partners.

A Bachelor's degree or equivalent practical experience is required, alongside 8 years of comprehensive software development experience.

Possess 5 years of experience in building and developing large-scale infrastructure, distributed systems, networks, or specialized compute technologies.

Demonstrated experience in designing, building, and operating large-scale distributed systems, emphasizing scalability, fault tolerance, and reliability.

Proficiency in designing and scaling distributed systems, data/ML pipelines, or developer platforms using languages such as C++, Python, Java, or Kotlin.

Familiarity with AI/ML evaluation frameworks, LLM/agentic orchestration, autoraters, prompt optimization, or large-scale experimentation infrastructure is essential.