AWS has just unveiled the newest AWS Certified Generative AI Developer – Professional certification. This important credential is for developers and AI professionals who want to advance their careers by building, deploying, and improving high-quality generative AI applications on AWS. This certification confirms your skills in using foundation models and integrating generative AI into practical business solutions.

This certification highlights a developer’s ability to effectively integrate foundation models, retrieval-augmented generation (RAG) architectures, and vector databases into production-ready AI solutions. While the complete exam guide has not yet been released, AWS has shared key insights through its official certification page and training announcement, providing an early opportunity for candidates to begin preparing for this cutting-edge addition to the AWS certification portfolio.

Overview of the AWS Certified Generative AI Developer Professional

The AWS Certified Generative AI Developer – Professional certification is a game-changer for seasoned professionals aiming to excel in the rapidly evolving field of generative AI. Set to open beta registration on November 18, 2025, this certification offers a comprehensive 204-minute exam consisting of 85 multiple-choice or multiple-response questions. The beta exam will cost $150 USD. It will initially be available in English and Japanese, allowing early candidates to be among the first to validate their expertise in this emerging domain.

With a minimum of two years of cloud experience and at least one year of practical work on generative AI projects, candidates will find this certification invaluable. A strong understanding of AWS compute, storage, networking, and security services is essential, along with knowledge of infrastructure as code (IaC), monitoring, and cost optimization techniques.

This certification underscores AWS’s significant investment in artificial intelligence and machine learning education. Moreover, with the planned retirement of the AWS Certified Machine Learning – Specialty exam in 2026, now is the ideal time to pursue this forward-looking generative AI credential. By earning this certification, you’ll position yourself at the forefront of innovation and opportunity within the evolving landscape of cloud-based AI development.

What Certifications Should You Earn Before Taking This Exam?

There are no formal prerequisites for the AWS Certified Generative AI Developer – Professional, meaning you can register for and take the exam without holding any prior AWS certifications. However, because this is a professional-level credential, AWS recommends that candidates first build a strong technical foundation across cloud architecture, artificial intelligence, and data engineering. Developing these baseline skills ensures you’ll be better equipped to understand and apply the advanced generative AI concepts covered in the exam.

Earning one or more of the following certifications can significantly enhance your readiness and provide a structured learning path toward mastering generative AI development on AWS:

• AWS Certified AI Practitioner – This certification is ideal for individuals beginning their journey into artificial intelligence and machine learning. It introduces the fundamental principles of AI, including generative AI, model lifecycle basics, and responsible AI practices. It also helps you understand how AWS services like Amazon Bedrock, SageMaker, and AI-driven APIs fit into broader solution architectures and workflows.

• AWS Certified Solutions Architect – Associate – This credential focuses on building a deep understanding of AWS’s core infrastructure services and architectural best practices. You’ll gain the ability to design secure, resilient, and cost-optimized systems, which is essential for deploying and scaling AI workloads efficiently in real-world environments.

• AWS Certified Machine Learning Engineer – Associate – This certification dives into the complete machine learning lifecycle on AWS—from data preparation and model building to training, tuning, deployment, and monitoring. The hands-on experience you gain with SageMaker and other ML tools directly supports the skills required for generative AI solutions, such as fine-tuning foundation models or managing large-scale inference.



• AWS Certified Data Engineer – Associate – Data serves as the backbone of every AI system, and this certification validates your expertise in data collection, transformation, and storage. You’ll learn to build and optimize data pipelines using AWS analytics services, an essential skill for feeding and maintaining generative AI models and retrieval-augmented generation (RAG) architectures.

By completing one or more of these certifications before attempting the AWS Certified Generative AI Developer – Professional, you will establish a well-rounded skill set that bridges cloud infrastructure, AI development, and data management. This foundation not only increases your chances of success in the exam but also ensures you can design, build, and scale generative AI applications with confidence in production environments.