UX Engineer, Applied AI

Minimum Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in a technical, UX, or design setting, or related experience.
• 8 years of experience working cross functionally with both internal and external stakeholders.

• 7 years of technical leadership experience.
• 5 years of experience managing projects.

At Google, we follow a simple but vital premise: "Focus on the user and all else will follow." Google’s UX Engineers are versatile and passionate about taking on new problems to drive progress and vision for design teams. They’re comfortable wearing many hats and get excited about working across discipline lines to develop products and prototypes that bring new ideas to life.

Google User Experience (UX) is made up of multi-disciplinary teams of UX Designers, Researchers, Writers, Content Strategists, Program Managers, and Engineers: we care deeply about the people who use our products. The UX team plays an integral part in gathering insights about the attitudes, emotions, and behaviors of people who use our products to inspire and inform design. We collaborate closely with each other and with engineering and product management to create industry‑leading products that deliver value for the people who use them, and for Google’s businesses.

As a UX Engineer, you'll work as part of a UX team in a challenging, fast‑paced environment. You’ll demonstrate your creativity, analytical skills, and knowledge of user‑facing technologies to create prototypes that identify the best product experiences, launch innovative features, build tools that accelerate UX teams, bridge between design and engineering discussions, and enable efficient, high‑quality execution.

In this role, you will build and ship AI experiences across Gemini, Search, and Workspace, focusing on driving enterprise growth through rapid prototyping. You will collaborate with cross‑functional partners to iterate on experimental models and frameworks, delivering high‑impact features. You will bridge the gap between early‑stage experiments and public deployment on global platforms.

Applied AI builds conversational agents deployed at