Google Cloud Certified Professional Agentic Architect

The Google Cloud Certified Professional Agentic Architect certification is transitioning from Beta to General Availability (GA), providing professionals with an opportunity to validate their expertise in designing, building, and deploying agentic AI solutions on Google Cloud.

The Professional Agentic Architect GA exam will launch in mid-November 2026, start preparing today!

• Professional-Level Certification: Validate your expertise in designing and architecting agentic AI solutions on Google Cloud.

• Agentic AI Expertise: Demonstrate your understanding of AI agents, agent orchestration, and multi-agent systems.

• Enterprise AI Architecture: Showcase your ability to design scalable, secure, reliable, and production-ready agentic AI solutions.

• Career Advancement: Strengthen your professional profile with a Google Cloud certification focused on agentic AI architecture.

• Industry-Relevant Skills: Build recognition for your ability to apply agentic AI concepts to real-world business and enterprise scenarios.

✓ Validate Your Expertise: Demonstrate your skills in designing and architecting agentic AI solutions on Google Cloud.

✓ Advance Your Career: Strengthen your professional credentials in the rapidly evolving field of agentic AI.

✓ Demonstrate Practical Knowledge: Showcase your understanding of AI agent architecture, orchestration, integration, and enterprise deployment.

✓ Support Professional Growth: Earn a Google Cloud professional certification that highlights your expertise in agentic AI architecture.

Agentic AI is moving beyond simple question-and-answer applications. Modern organizations are looking at AI agents that can reason through tasks, use tools, retrieve enterprise information, coordinate with other agents, and take action on behalf of users.

That shift creates a need for professionals who understand more than just LLMs and prompting. They need to know how to design the complete agentic workflow and operate it responsibly in production.

This course helps you build that broader understanding by covering:

• Low-code agent development using Gemini Enterprise tools

• Coding agents for application development

• Custom agent development with ADK and related tools

The course is aligned with the five major skill areas covered by the certification:

1. Build agents using low-code tools

2. Use coding agents for application development

3. Develop custom agents

4. Evaluate and deploy agentic workflows

5. Secure and govern agentic workflows

Section 1: Building Agents Using Low-Code Tools:

This section establishes the foundation for creating useful enterprise agents using low-code capabilities. Learn how to create and configure agentic workflows without building every component from scratch. You will learn how to:

• Configure state-based workflows using pages, transition routes, & event handlers

• Configure agent behavior using Gemini Enterprise tools

• Work with Gemini Enterprise Agent Designer

• Work with Customer Experience Agent Studio (CX Agent Studio)

By completing this course, you will be able to:

• Build AI agents using low-code Google Cloud tools

• Configure state-based agentic workflows

• Connect agents to enterprise and multimodal data

• Use coding agents as part of application development

• Configure MCP servers, tools, skills, and subagents

The course covers the technologies and services identified as in scope for the certification exam.

• Agent Development and Runtime

• Agent Security and Governance

• Agent Communication and Integration

• Gemini and AI Services

This certification is aimed at experienced developers and architects working with AI, software development, and Google Cloud.

Learners will benefit from experience with:

• Software development and application architecture

• Large language models and generative AI

• Agentic AI concepts and design patterns

• Writing and understanding code

There are no specific prerequisites listed in the provided certification reference material. However, a strong foundation in the following areas will help you get more from the course:

• Generative AI and LLM fundamentals

• Agentic AI concepts

• Programming fundamentals

• APIs and application integration

• Cloud computing

This course is suitable for professionals who want to design, develop, deploy, and manage production-ready agentic AI solutions on Google Cloud.

It is particularly relevant for:

• AI and Machine Learning Engineers

• Generative AI Developers

• Agentic AI Developers

• Cloud and AI Architects

• Solutions Architects

• Enterprise Knowledge Assistants

• Multi-Agent Business Workflows

• AI-Powered Software Development

• Intelligent Customer Experiences

By learning the Professional Agentic Architect skill set, you can:

• Build a stronger foundation in production-focused agentic AI

• Understand both low-code and code-based agent development

• Work with modern coding agents and agent development frameworks

• Build custom agents using ADK

• Design enterprise RAG and retrieval workflows

Certification-Aligned Learning

The course follows the five major areas covered in the Professional Agentic Architect certification, helping learners focus their preparation around the exam objectives.

Practical Agent Development

Learn how agents are designed, configured, integrated, evaluated, deployed, and secured rather than focusing only on theoretical concepts.

Low-Code and Code-Based Approaches

Explore both Gemini Enterprise low-code capabilities and code-based agent development using tools such as ADK and Agents CLI.

Enterprise-Focused Architecture

Understand how agents interact with enterprise data, databases, APIs, SaaS platforms, tools, and other agents.

Evaluation and Production Readiness

Go beyond development by learning how to test, evaluate, monitor, troubleshoot, and optimize agentic applications.

Security and Governance

Learn how identity, authentication, guardrails, policies, gateways, and human oversight can be incorporated into agentic workflows.

Knowledge of agentic AI architecture can support roles involved in designing and implementing AI-powered applications and cloud platforms. Potential career paths include:

• Agentic AI Architect

• AI Solutions Architect

• Generative AI Engineer

• AI and Machine Learning Engineer

• Cloud AI Architect