Staff Applied AI Agent Engineer

Google•Kirkland, WA

1d•$207,000 - $300,000

About The Position

Google is seeking an engineer to apply generative AI to customer problems by building, deploying, and optimizing AI agents on its Gemini for Customer Experience platform. The role is embedded with strategic customer accounts and connects core product engineering teams with complex customer needs, accelerating customer success and informing the evolution of Google’s AI products. The Cloud Applied AI team supports business growth with Gemini Enterprise and a portfolio of customer experience products and packaged solutions. The team focuses on high adoption and fast time to value, delivering quickly deployed solutions and new capabilities while collaborating with model builders in a fast-paced, collaborative environment. Individual pay is determined by job-related skills, experience, and relevant education or training. The stated US pay range is $207,000–$300,000, plus a 20% bonus target, equity, and benefits.

Requirements

Bachelor’s degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience testing and launching software products.
3 years of experience with software design and architecture.
5 years of experience in cloud computing or a technical customer-facing role.
Experience developing and deploying agentic solutions using tools, multi-agent workflows, and RAG systems.
Experience managing customer projects and resources.

Nice To Haves

Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
5 years of experience with data structures and algorithms.
Experience in prompt development, model evaluation, and creative applications of artificial intelligence.
Experience designing end-to-end secure, observable multi-agent systems using complex design patterns such as ReAct and self-reflection, state management, and tool-calling protocols.
Experience designing intuitive interfaces for complex AI and agentic systems, prioritizing context engineering, transparency, and explainability to foster user trust.
Experience architecting AI solutions within complex infrastructures while ensuring data sovereignty and secure governance.

Responsibilities

Partner with select strategic customers to understand their business issues and design, co-develop, debug, and deploy custom conversational AI agents and solutions.
Write bespoke code, develop custom tooling, and contribute to core product code when needed to resolve critical customer issues.
Turn learnings from customer engagements into reusable tools, documentation, accelerators, and organizational best practices.
Share field insights with core Product and Development teams to influence product strategy and identify feature gaps.
Provide customers with technical guidance and best practices on agent improvement, performance tuning, CI/CD pipelines, and production readiness.