AWS Generative AI Developer Professional Certification Guide 2026 | K21Academy

AWS Introduces New AWS Certified GenAI Developer Certification—The AWS Generative AI Developer – Professional credential is a timely and high-value certification for professionals who want to specialize in generative AI development on the AWS cloud. It helps you demonstrate you can go beyond proof of concept into building scalable, secure, cost-efficient, production-ready Gen AI solutions.

Note: Beta registration for the certification opens on November 18, 2025.

This blog will cover everything you need to know about the AWS Generative AI Developer certification.

What is the AWS Generative AI Developer – Professional certification [GDP-C01]?

This certification (currently in beta) is a professional-level credential from AWS designed to validate advanced technical skills in building, deploying and operating production-ready generative AI solutions on the AWS platform.

• Designed for developers/engineers who have experience with AWS and want to work with generative AI (Gen AI) solutions (foundation models, retrieval-augmented generation, agents, etc.).
• The certification assists businesses in finding experts who can deploy generative AI in production while addressing issues related to cost, security, governance, and scalability.
• This credential indicates that you can work with AWS’s Gen AI services (such as Amazon Bedrock, SDKs, model invocation, deployment, and observability) and create genuine business value, which is important given the growing importance of generative AI in enterprise applications.

Who is a “Generative AI Developer”?

Before diving into the certification, it helps to define what is meant by “Generative AI Developer”.

A specialist in generative AI development is someone who:

• comprehends, handles, and applies foundation models—such as large language models, vision, and multimodal models—in applications.
• creates and implements generative-AI applications, such as conversational agents, business workflows, RAG (retrieval-augmented generation) systems, and content generation (text, images, and code).
• incorporates generative models into production pipelines and uses quick engineering or fine-tuning/adapter approaches as needed.
• deploys models at scale (via cloud services, APIs, and containers) and manages Gen AI system security and governance, observability, cost optimisation, and monitoring.
• interactions with the infrastructure (computing, storage, networking), user interfaces (chatbots, embedded stores, knowledge bases), application logic, and data pipelines.

In an AWS context, a Gen AI developer would likely use services such as Amazon Bedrock, Amazon SageMaker, Amazon Q (developer assistant), storage (S3), compute (EC2/Lambda/Fargate), orchestration (Step Functions/EventBridge), embedding/knowledge base services, and apply prompt/agent patterns.

Related Readings: Amazon Web Services

Who Should Take the AWS Generative AI Developer Professional Certification?

This certification is ideal for experienced developers, machine learning engineers, and cloud architects who have at least two years of hands-on AWS experience and some exposure to generative AI solutions.This certification is ideal for experienced developers, machine learning engineers, and cloud architects who have at least two years of hands-on AWS experience and some exposure to generative AI solutions.

• It is intended for professionals who wish to use services like Amazon Bedrock, SageMaker, and AWS Lambda to develop, implement, and oversee production-grade Gen AI systems.
• This certification is ideal if you’re already creating AI-driven chatbots, RAG-based systems, or automated content creation tools and you’re prepared to expand your knowledge of foundation models and AI architecture.
• It’s also a great fit for those in charge of AI projects in businesses trying to safely and effectively expand their generative AI capabilities. If you’re exploring ways to enhance your AI journey, you should also check out the best AI tools for web developers, a collection of powerful, time-saving platforms that can make your AI and development workflow smarter, faster, and more innovative.

What Certifications Should You Earn Before Taking This Exam?

Although there are no official prerequisites for the AWS Certified Generative AI Developer – Professional test, holding foundational or associate-level AWS credentials will greatly facilitate your preparation.

You can develop a strong grasp of AWS services, AI/ML principles, and deployment procedures by obtaining certifications such as the AWS Certified Cloud Practitioner, AWS Certified AI Practitioner, or AWS Certified Machine Learning Engineer – Associate. Prior to taking on the challenging, scenario-based questions of the Professional-level Gen AI exam, these certificates educate you the fundamental cloud and AI principles. To put it briefly, consider these your stepping stones to becoming an expert in AWS generative AI programming.

AWS Generative AI Developer Certification: Exam Overview

AWS GDP-C01 Exam Domains

The AWS Generative AI Developer certification exam includes a complete list of exam domains, task statements, and knowledge areas.

Domain 1: Getting Started with AWS Generative AI for Developers

This exam domain focuses on the:

• Basic understanding of generative AI and the distinctions between AI, ML, and DL
• What are Foundation Models (FMs) and Large Language Models (LLMs) and what are they used for?
• The main elements of the Amazon Bedrock service are the prompts, inference, responses, and application of Amazon
• Bedrock utilising Foundation Models (FMs) to produce output such as text, images, and code.
• Overview of the Amazon Q Developer Service and its applications
• How GenAI may improve the lifecycle of software development

Related Readings: Deep Learning Vs Machine Learning

Domain 2: Generative AI Applications with Amazon Bedrock

In this domain, you explore Amazon Bedrock Knowledge Bases, a feature that allows you to apply the complete RAG workflow, from retrieval and prompt augmentation to ingestion. In order to give your apps context-aware, domain-specific AI interactions, the course teaches you how to build and maintain knowledge bases.

The course covers Amazon Bedrock Flows and Amazon Bedrock Prompt Management, showing you how to develop workflows that chain several AI processes and produce versioned, reusable prompt templates. You gain knowledge of Amazon Bedrock Agent configuration and deployment, generative AI (agentic AI) agents for task automation, and how to integrate agents with other tools to build more self-sufficient systems.

Related Readings: Enable foundation models in AWS Bedrock

Domain 3: Amazon Bedrock Customization, Optimization & Automation

In this domain, you learn optimising, automating, and personalising your AI solutions to increase productivity. You study model modification strategies, including fine-tuning and continuing pre-training. The course delves deeply into advanced optimisation techniques, such as using prompt caching to optimise response times and collaborating with Amazon Bedrock Evaluations to complete evaluation jobs that compare and evaluate model performance. In the automation portion, you learn how to use Amazon Bedrock Data Automation to process and modify huge datasets in order to streamline AI workflows. You come across several instances of automating operations with Amazon Q Developer on the command line.

Related Readings: Develop & Manage Generative AI Applications on AWS with Bedrock and LangChain

Conclusion

For developers who want to focus on next-generation AI applications, earning the AWS Generative AI Developer Professional Certification is a significant accomplishment. This certification attests to your ability to develop, implement, and scale practical generative AI solutions on AWS as generative AI transforms a variety of industries, from intelligent assistants to content automation.

In essence, this certification bridges the gap between AI innovation and enterprise implementation. Earning it positions you at the forefront of the AI revolution—equipped to design intelligent solutions that go beyond prototypes and deliver true business impact.