Minimum qualifications:

• Bachelor's degree in Computer Science or equivalent practical experience.
• 5 years of experience building and developing large-scale infrastructure or distributed systems.

Preferred qualifications:

• Experience programming in C, C++, Java or Python.
• Experience building or optimizing inference systems for Large Language Models (LLMs) or multimodal models (audio/video).
• Experience implementing trust and safety features, abuse detection classifiers, or data residency controls.
• Experience designing unified APIs or middleware that abstracts complexity for other developers.
• Track record of debugging production issues in high-throughput, low-latency environments.

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.

The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.

Responsibilities:

• Design, develop, and deploy scalable software infrastructure to unify and serve large language and multimodal models across cloud environments.
• Implement responsible AI, engineering real-time safety filters, abuse detection mechanisms, and compliance controls directly into the serving stack to ensure secure and ethical AI usage.
• Drive improvements in system latency, efficiency, and stability. Identify bottlenecks and resolve production issues.
• Collaborate closely with research scientists and global engineering teams to transform cutting-edge model breakthroughs into robust, enterprise-ready products.
• Write high-quality, testable, and maintainable code while contributing to technical design reviews and engineering best practices.