Senior Azure AI Cloud Engineer

Introduction & Summary

As the Senior Azure Cloud Engineer with GCP exposure, you will be responsible for the design, implementation, and optimization of scalable cloud infrastructure on Azure platforms. This position emphasizes deploying and maintaining applications focused on AI and Data platforms, ensuring high availability, security, and performance. The ideal candidate will demonstrate strong knowledge of Azure services, hands-on infrastructure-as-code expertise, particularly with Terraform, and a passion for enabling AI/ML workloads.

Main Responsibilities

• Design and implement secure, scalable cloud infrastructure using Azure services with a focus on AI workloads.
• Develop automated deployment pipelines using Infrastructure-as-Code tools like Terraform.
• Implement security practices such as Identity and Access Management and network security.
• Design and manage Azure AI and Data platform components to support AI projects.
• Collaborate with data science and engineering teams for effective model development environments.
• Utilize AI tools to enhance infrastructure operations and troubleshooting.
• Create and maintain documentation of infrastructure configurations.
• Collaborate with architects and managers for expedited MVP developments.
• Stay updated with new Azure services and provide recommendations for improvements.

• Bachelors degree in IT, Computer Science, Business Administration, or related field; Masters degree or certifications preferred.
• Minimum of 8 years of experience in cloud engineering or architecture.
• Proven experience with Azure services, including virtual machines, storage solutions, and databases.
• Hands-on experience with Infrastructure-as-Code tools such as Terraform.
• Strong scripting skills in Python, Bash, or PowerShell.
• Familiarity with CI/CD tools and their integration with Azure.
• Knowledge of networking fundamentals as related to Azure environments.
• Proficiency in monitoring and logging tools, both native and third-party.
• Familiarity with AI coding assistants and frameworks is a plus.
• Understanding of cybersecurity principles and best practices in cloud environments.

• Experience with cybersecurity practices in cloud settings.
• Certifications like GCP/Azure Certified DevOps Engineer or Solutions Architect.

This role is expected to be remote, with a focus on projects involving advanced AI and data workloads. The successful candidate will engage in a dynamic and collaborative cloud engineering environment.