EnglishDeutschFrançaisEspañolPortuguês

AWS · AIP-C01 · Advanced

AWS Certified Generative AI Developer - Professional

Validates ability to integrate foundation models into applications and implement GenAI solutions using AWS technologies including Amazon Bedrock, SageMaker AI, and agentic AI patterns. 75+ AI-generated practice questions with explanations. Free trial, pass guarantee.

Start Free Trial

7-day free trial, no credit card required

75 Questions
180min Time Limit
750/ 1000 Pass Score
$300 Exam Fee

Overview

About the exam

The AWS Certified Generative AI Developer – Professional validates advanced expertise in building, deploying, and optimizing production-grade generative AI applications on AWS. It covers solution design using foundation models, implementing generative AI with Amazon Bedrock and SageMaker, retrieval-augmented generation architectures, API integration, and security and governance for AI systems.

This certification is designed for developers and architects with at least one year of hands-on experience implementing generative AI solutions on AWS. It is distinct from the foundational AIF-C01, focusing on practical implementation of generative AI applications using AWS services.

Exam Domains

What's on the exam

The exam consists of 75 questions (65 scored, 10 unscored) over 180 minutes, featuring multiple-choice and multiple-response question types. Questions are deeply scenario-based, covering Bedrock integration, RAG architecture design, model customization, and production deployment patterns. Budget 2.4 minutes per question and manage time carefully.

Foundation Model Integration, Data Management, and Compliance 31%
Implementation and Integration 26%
AI Safety, Security, and Governance 20%
Operational Efficiency and Optimization for GenAI Applications 12%
Testing, Validation, and Troubleshooting 11%

Format

What to expect

multiple choice
65%
multiple response
35%

Watch out

Where candidates struggle

This professional-level exam requires hands-on generative AI implementation experience. Candidates must go beyond conceptual understanding to demonstrate practical ability to build, optimize, and secure production generative AI systems.

  1. 01
    Bedrock Configuration — Not understanding Bedrock model selection, inference parameters, guardrails configuration, and knowledge base integration for different generative AI use cases.
  2. 02
    RAG Architecture — Misunderstanding vector store selection, embedding model choices, chunking strategies, and retrieval pipeline design for retrieval-augmented generation.
  3. 03
    Model Customization — Confusing when to use prompt engineering, fine-tuning, continued pre-training, or distillation for different model customization requirements.
  4. 04
    Cost Management — Not understanding token-based pricing, provisioned throughput, model selection trade-offs, and caching strategies for optimizing generative AI costs.
  5. 05
    AI Governance — Overlooking guardrails, content filtering, PII handling, and audit logging requirements for production generative AI applications.

Details

Exam logistics

Delivered via Pearson VUE online or at testing centers. Available in English and Japanese; additional languages may be added over time. The certification is valid for 3 years with renewal through recertification exams.

Delivery Pearson VUE testing center or online proctored exam
Retake policy 14-day waiting period between exam attempts, no limit on total number of attempts
Validity 3 years
Career outcomes Generative AI developer, AI solutions architect, ML platform engineer, and senior software engineer roles building production generative AI applications on AWS
Renewal Pass a recertification exam before the 3-year expiration date. Professional-level certifications also renew all associate-level certifications
Study time ~85 hours
Official guide View on vendor site

Ready to pass?

Join thousands of professionals who passed with AI-powered practice.

Start Free Trial