GenAI on Google Cloud

In today's AI landscape, success depends not just on prompting large language models but on orchestrating them into intelligent systems that are scalable, compliant, and cost-effective. GenAI on Google Cloud is your hands-on guide to bridging that gap. Whether you're an ML engineer or an enterprise leader, this book offers a practical game plan for taking agentic systems from prototype to production.

Written by practitioners with deep experience in AgentOps, data engineering, and GenAI infrastructure, this guide takes you through real-world workflows from data prep and deployment to orchestration and integration. With concrete examples, field-tested frameworks, and honest insights, you'll learn how to build agentic systems that deliver measurable business value.

• Bridge the production gap that stalls 90% of vertical AI initiatives using systematic deployment frameworks
• Navigate AgentOps complexities through practical guidance on orchestration, evaluation, and responsible AI practices
• Build robust multimodal systems for text, images, and video using proven agent architectures
• Optimize for scale with strategies for cost management, performance tuning, and production monitoring

Ayo Adedeji is a Senior Developer Relations Engineer on Google Cloud's AI Platform team and specializes in bridging advanced AI technologies with practical developer solutions. With a background as an ML Engineer in healthcare, Ayo's expertise spans computational biology, big data processing, and foundation models. He holds engineering degrees from Stanford and Johns Hopkins and is passionate about helping developers across industries harness the power of Google Cloud to build innovative, responsible AI solutions. Lavi Nigam is a Machine Learning Engineer and AI/ML Advocate at Google, passionate about democratizing AI and making it accessible to all. He currently leads the charge in bringing Gemini, Google's cutting-edge generative AI model, to developers worldwide through the Google Cloud Vertex AI ecosystem. In addition, he is focused on building scalable LLMOps and Generative AI Agents design patterns to help enterprises efficiently use, manage, and deploy these powerful models. His deep understanding of MLOps and Google Cloud's infrastructure empowers him to guide businesses in building robust, scalable, and production-ready AI systems. He is a recognized thought leader in the field, named one of the "40 Under 40 Data Scientists" by Analytics India Magazine. Sarita Joshi, an AI/ML Engineer at Google Cloud, Senior IEEE member, empowers healthcare organizations to achieve transformative outcomes with AI. Her expertise is built on years of leading AI initiatives at Google and Amazon Web Services, where she served as Senior Science Manager and spearheaded customer transformations. With a background spanning consulting, R&D, and product engineering at industry giants like Amazon, Accenture, and Philips Healthcare, Sarita brings a unique blend of technical acumen and strategic vision. Her contributions extend to the research community through speaking engagements and peer review work at leading AI conferences such as ACM, NeurIPS, AAAI, and IEEE. Sarita holds a Master's degree in Computer Science from Northeastern University, equipping her with the knowledge and experience to guide others in navigating the complexities of AI in healthcare. Stephanie Gervasi is a Senior Customer Engineer in AI/ML with Google Cloud. Steph has worked in academia, industry, and in the non-profit sector to imagine, build, and deploy AI/ML solutions. She has managed and led strategy development for Data Science and Predictive Analytics teams and created the first Responsible AI Playbook and Technical Toolkit for Fair AI at a national health payer organization. Steph has given local and international talks on AI/ML and has over 25 peer-reviewed publications, including collaborative research papers with academic institutions such as MIT and the University of Pennsylvania. Steph received a PhD in Infectious Disease Dynamics from Oregon State University and a Master's in Ecological Sciences from the University of Michigan.