Join the Google Cloud Platform team and empower customers to build what's next with cutting-edge cloud technology. Our secure, reliable, and scalable products support the full tech stack, assisting businesses, educational institutions, and government agencies in leveraging technology to connect and thrive. As an entrepreneurial member of our rapidly expanding team, you'll be instrumental in understanding client needs and shaping the future of business technology.

This Cloud AI Engineer role focuses on enhancing the adoption of Gemini Enterprise and the broader Google Cloud Agentic AI suite for strategic customers. You will be responsible for designing and implementing robust, production-ready application architectures, leveraging Gemini Enterprise and core Google AI products to address customer use cases. Your work will involve collaborating with customers to identify opportunities for workflow transformation through autonomous agents, proactively removing technical obstacles to ensure successful deployment and high adoption rates.

Google Cloud is dedicated to accelerating digital transformation for organizations globally, delivering enterprise-grade solutions powered by Google's technology and tools for sustainable development. Customers worldwide rely on Google Cloud as a trusted partner for growth and solving critical business challenges.

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

Act as a trusted technical advisor to C-suite executives at key global accounts, guiding their AI strategy and accelerating Gemini Enterprise adoption.

Translate intricate architectural challenges into actionable requirements for Google's engineering teams, influencing the core product roadmap.

Deliver best-practice recommendations and present technical solutions to executive boards and stakeholders to achieve significant technical wins.

Serve as a thought leader and mentor within the Google Cloud organization, enhancing engineer technical expertise and establishing best practices for agentic AI architectures.

Essential qualifications include a Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience. You should possess 6 years of experience in software engineering, enterprise cloud architecture, or technical consulting.

Candidates must have 3 years of experience in advanced AI/ML architecture, deploying generative AI applications, intelligent agents, or LLM-powered solutions globally. Proficiency in Python, including the implementation and deployment of tiered microservices applications, is required. Additionally, experience deploying production-grade cloud infrastructure or architecting and building cloud-based data solutions such as enterprise data warehouses, data lakes, and data pipelines is necessary.

Preferred qualifications include a Bachelor’s, Master’s, or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience pioneering multimodal AI solutions, a deep understanding of AI security, LLM governance, and enterprise guardrails, and excellence in architecting resilient RAG systems are highly valued. Recognized industry thought leadership in Generative AI, agentic workflows, or large-scale cloud data infrastructure is also a plus.