As a Microsoft Azure AI engineer, you build, manage, and deploy AI solutions that make the most of:
- Azure Cognitive Services.
- Azure Applied AI services.
Your responsibilities include participating in all phases of AI solutions development, including:
- Requirements definition and design
- Development
- Deployment
- Integration
- Maintenance
- Performance tuning
- Monitoring
You work with solution architects to translate their vision and with data scientists, data engineers, Internet of Things (IoT) specialists, infrastructure administrators, and other software developers to build complete end-to-end AI solutions.
As an Azure AI engineer, you have experience developing solutions that use languages such as:
You should be able to use Representational State Transfer (REST) APIs and SDK to build secure image processing, video processing, natural language processing, knowledge mining, and conversational AI solutions on Azure. You should be familiar with all methods of implementing AI solutions. Plus, you understand the components that make up the Azure AI portfolio and the available data storage options. As an Azure AI engineer, you also need to understand and be able to apply responsible AI principles.
Important
The English language version of this certification was updated on August 23, 2023. Review the study guide linked on the Exam AI-102 page for details about recent changes.
Note
Cognitive Services has been renamed to Azure AI Services. Individual services have also been renamed. These changes will appear on the exam in late 2023. Learn more about Azure AI services.