Join the Google Cloud Platform team and empower customers to build the future with cloud-native technology. This role offers a chance to be at the forefront of AI innovation, working with cutting-edge products like Gemini Enterprise.

As a Cloud AI Engineer, you'll guide strategic clients in adopting Gemini Enterprise and the broader Google Cloud Agentic AI suite. Your expertise will be crucial in designing and implementing robust application architectures that leverage Google's AI capabilities to address complex customer use cases and workflows.

Google Cloud is dedicated to accelerating digital transformation across industries worldwide. We provide enterprise-grade solutions powered by Google's advanced technology, helping developers create more sustainably and enabling businesses to solve critical challenges.

Spearhead the delivery and implementation of Gemini Enterprise solutions, using Agent Development Kits (ADKs) to resolve complex, enterprise-scale technical challenges for customers.

Serve as a trusted technical advisor to Google's key clients, shaping their AI strategies and driving the adoption of Gemini Enterprise.

Provide architectural insights for existing product issues, collaborate with engineering teams to address gaps, and design scalable workarounds for challenging edge cases.

Present best practices and technical information tailored for diverse business and technical stakeholders, including C-suite executives, to proactively encourage Gemini Enterprise adoption and user enablement.

A Bachelor's degree in Computer Science or a related technical discipline, or equivalent practical experience, is required.

Possess at least 3 years of experience in software engineering, cloud architecture, or technical consulting, with a minimum of 2 years focused on building and deploying GenAI applications, intelligent agents, or LLM-powered solutions.

Demonstrated experience in building and orchestrating agents using frameworks like ADKs, LangChain, LlamaIndex, and AutoGen. Proficiency in designing modern application architectures, including API design, microservices, and integrating AI models into existing enterprise systems is essential.

Strong command of Python is a prerequisite for this role.