Azure AI Cloud Engineer
Summary
Designs and implements secure, scalable Azure cloud infrastructure (with GCP exposure) focused on AI and data platforms. Automates deployments via Terraform, manages Azure AI services, collaborates with data teams to enable production AI/ML workloads, and handles security and monitoring.
Role Overview:
As the Azure Cloud Engineer with exposure to GCP, you will play a critical role in designing, implementing, and optimizing scalable and resilient cloud infrastructures on Azure platforms. This position requires deploying, automating, and maintaining cloud-based applications, services, and tools with a specific focus on AI and Data platform infrastructure, ensuring high availability, security, and performance. The ideal candidate will possess extensive knowledge of Azure services and architecture best practices, hands-on expertise with infrastructure-as-code (preferably Terraform), and a keen interest in AI/ML workload enablement, automation, monitoring, and troubleshooting.
Main Responsibilities
Key responsibilities include:
- Designing and implementing secure, scalable, and highly available cloud infrastructures using GCP/Azure services with a focus on AI, Analytics, and data-intensive workloads.
- Developing automated deployment pipelines using Infrastructure-as-Code tools such as Terraform, ensuring efficient and consistent infrastructure deployments.
- Managing security practices to ensure data protection and compliance with industry standards.
- Provisioning and managing Azure AI and Data platform components to support AI exploration and production deployment.
- Collaborating with data science and engineering teams to design governed AI environments that accelerate model development.
- Utilizing AI tools and practices to enhance productivity in coding, debugging, and documenting infrastructure.
- Maintaining comprehensive documentation of infrastructure architecture and configurations.
- Collaborating with cross-functional architects to facilitate quick MVP development.
- Staying updated with new GCP/Azure services and providing recommendations for improvements.
Key Requirements
- Bachelor's degree in information technology, Computer Science, or related fields; Master's degree or relevant certifications preferred.
- Minimum of 5 years in cloud engineering or related fields, with experience in data or AI/ML.
- Proven experience with GCP/Azure services, including various storage and compute services, as well as experience deploying Azure AI services.
- Hands-on experience with Infrastructure-as-Code tools, notably Terraform.
- Strong scripting skills in Python, Bash, or PowerShell.
- Familiarity with CI/CD tools and cloud networking fundamentals.
- Proficiency in monitoring and logging tools.
- Familiarity with agentic AI systems is a plus.
Nice to Have
- Certification in GCP/Azure platforms.
- Experience with cybersecurity principles and frameworks.
- Familiarity with DevOps practices and methodologies.
Other Details
This position is based in Koregaon Park, Pune, and follows a hybrid working model, requiring in-office attendance three days a week. Work hours align with the CET time zone (9 hours).