Azure AI Cloud Engineer - Mid Level
Summary
Designs and implements scalable Azure cloud infrastructure with a focus on AI and Data platforms, using Infrastructure-as-Code (Terraform), scripting, and security best practices to deliver highly available environments for data science teams.
The Azure Cloud Engineer is responsible for designing, implementing, and optimizing scalable cloud infrastructure on Azure platforms, focusing on AI and Data solutions to enhance availability, security, and performance.
Responsibilities:
Design and implement secure, scalable, and highly available cloud infrastructure using GCP/Azure services.
Develop automated deployment pipelines using Infrastructure-as-Code (IaC) tools.
Implement and manage security practices to ensure data protection and compliance.
Design and provision AI and Data platform components via IaC.
Collaborate with data science and engineering teams to deliver AI environments.
Leverage AI tools and practices to enhance productivity.
Create and maintain comprehensive documentation of infrastructure architecture.
Stay updated with new GCP/Azure services and best practices.
Must Haves:
Bachelor’s degree in IT, Computer Science, or related field.
5-7 years of experience in cloud engineering/architecture.
Strong expertise in GCP/Azure services.
Hands-on experience with Terraform and Infrastructure-as-Code.
Proficiency in scripting languages (Python, Bash, PowerShell).
Understanding of cybersecurity principles and practices.
Nice to Haves:
Master's degree or relevant certifications.
Experience with modern AI tools and frameworks.
Familiarity with CI/CD tools.
Proficiency in monitoring tools like Datadog or Splunk.
Knowledge of network fundamentals in GCP/Azure.
Other Details:
Location: Koregaon Park, Pune.
Work model: Hybrid (3 days/week in office).
Work hours: CET Time zone (9 hours).