As a Microsoft Azure AI engineer, you build, manage, and deploy AI solutions that leverage Azure AI.

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. You also work with data scientists, data engineers, Internet of Things (IoT) specialists, infrastructure administrators, and other software developers to:

• Build complete and secure end-to-end AI solutions.
• Integrate AI capabilities in other applications and solutions.

As an Azure AI engineer, you have experience developing solutions that use languages such as:

• Python
• C#

You should be able to use Representational State Transfer (REST) APIs and SDKs to build secure image processing, video processing, natural language processing, knowledge mining, and generative AI solutions on Azure. You should:

• Understand the components that make up the Azure AI portfolio and the available data storage options.
• Be able to apply responsible AI principles.

As a candidate for this certification, you should have subject matter expertise in implementing, managing, and monitoring an organization’s Azure environment, including:

• Virtual networks
• Storage
• Compute
• Identity
• Security
• Governance

As an Azure administrator, you often serve as part of a larger team dedicated to implementing an organization’s cloud infrastructure. You also coordinate with other roles to deliver Azure networking, security, database, application development, and DevOps solutions.

You should be familiar with:

• Operating systems
• Networking
• Servers
• Virtualization

In addition, you should have experience with:

• PowerShell
• Azure CLI
• The Azure portal
• Azure Resource Manager templates
• Microsoft Entra ID