Join the Google Cloud Platform team, empowering customers to innovate and build next-generation solutions in the cloud. Our robust, secure, and scalable products support businesses of all sizes, educational institutions, and government agencies. As an entrepreneurial member of this dynamic team, you'll play a vital role in understanding client needs and shaping the future of how businesses leverage technology to connect.

This Cloud AI Engineer position focuses on ensuring strategic customers achieve optimal adoption of Gemini Enterprise and the broader Google Cloud Agentic AI suite. You will architect and implement production-ready solutions, utilizing Gemini Enterprise and core Google AI products to address customer use cases. Your expertise will be crucial in identifying opportunities to transform workflows with autonomous agents and in proactively removing technical obstacles to drive successful deployments and high adoption rates. You'll leverage Google's advanced technology to monitor performance, debug complex agent behaviors, and meet customer and partner requirements, leading the end-to-end execution of Google Cloud Platform solution adoption.

Lead global delivery and implementation of Gemini Enterprise solutions, tackling complex, enterprise-scale technical challenges using Agent Development Kits (ADKs).

Serve as a trusted technical advisor to C-suite executives at Google’s top global accounts, influencing their AI strategy and accelerating Gemini Enterprise adoption.

Contribute to the core product roadmap by translating intricate architectural challenges into actionable requirements for Google's engineering teams.

Deliver expert best practice recommendations and high-impact technical presentations to executive boards and key stakeholders to secure large-scale technical successes.

Act as a thought leader and mentor within the Google Cloud organization, enhancing engineers' technical capabilities and establishing best practices for agentic AI architectures.

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

We seek individuals with at least 6 years of experience in software engineering, enterprise cloud architecture, or technical consulting.

Demonstrated experience of 3+ years in advanced AI/ML architecture, including deploying generative AI applications, intelligent agents, or LLM-powered solutions globally, is essential.

Proficiency in Python, including implementation and deployment of tiered microservices applications, is a must.

Experience deploying production-grade cloud infrastructure or architecting and building cloud-based data solutions, such as enterprise data warehouses, data lakes, data pipelines, and associated technologies, is necessary.

Preferred qualifications include a Bachelor’s, Master’s, or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience with multimodal AI solutions, AI security, LLM governance, enterprise guardrails, global compliance, architecting resilient RAG systems, and securely connecting LLMs with legacy databases is highly valued. Recognized industry thought leadership in Generative AI, agentic workflows, or large-scale cloud data infrastructure is a significant advantage.