Azure AI Cloud Engineer

As the Azure Cloud Engineer (with GCP exposure), you will be responsible for designing, implementing and optimizing scalable, resilient cloud infrastructure of Azure platforms. This role involves deploying, automating, and maintaining cloud-based applications, services and tools – which increase focus on AI and Data platform infrastructure- to ensure high availability, security and performance. The ideal candidate will have strong and depth knowledge of Azure services and architecture best practices, hands-on infrastructure-as-code expertise (especially Terraform), and a growing interest in enabling AI/ML workloads, infrastructure automation, monitoring and troubleshooting. Experience supporting AI projects and using modern AI tools to accelerate infrastructure work is highly valued.

Work Location: Koregaon Park, PuneWork model: Hybrid working (3 days / week in office)
Work hours: CET Time zone (9 hours)

Goals and deliverables

We count on you for:

• Design and implement secure, scalable and highly available cloud infrastructure using GCP/Azure services, based on business and technical requirements, with emphasis on enabling AI, Analytics, and data-intensive workloads.
• Develop automated deployment pipelines using Infrastructure-as-Code (IaC) tools such as Terraform, ensuring efficient and consistent infrastructure deployments.
• Implement and manage security practices to ensure data protection and compliance with industry standards and regulations.
• Design, provision, and manage Azure AI and Data platform components to support AI exploration and production deployment.
• Collaborate with data science, AI engineering, and data teams to implement AI Landing zones for accelerated model development.
• Leverage AI tools and practices to enhance productivity in infrastructure tasks.
• Create and maintain comprehensive documentation of infrastructure architecture and processes.
• Collaborate with architects and managers to ensure quick MVP delivery into production.
• Stay updated with new GCP/Azure services and best practices, especially in the AI and Data domains.

Education and experience

• Bachelor’s degree in information technology, Computer Science, or related field. A Master's degree or relevant certifications would be a plus.
• Minimum of 8-10 years of experience in cloud engineering or architecture, especially with data or AI/ML workloads.
• Proven experience with GCP/Azure services and deploying Azure AI services via Infrastructure-as-Code.
• Hands-on experience with Infrastructure-as-Code tools such as Terraform, and the ability to codify complex AI/data platforms.

• Strong scripting skills in Python, Bash or PowerShell.
• Familiarity with CI/CD tools and experience integrating them with GCP/Azure.
• Knowledge of networking fundamentals and secure connectivity patterns for AI services.
• Proficiency in monitoring tools, both native cloud and third-party.
• Familiarity with agentic AI systems or AI coding assistants is a distinct plus.

Cybersecurity Expertise:
• Understanding of cybersecurity principles and frameworks.
• Knowledge of encryption, identity management, and access controls within cloud environments.
• Preferably with relevant GCP/Azure certifications.

Skills and behavioral competencies:
• Excellent problem-solving and troubleshooting abilities.
• Result-oriented with strong influence and impact skills.
• Ability to work independently and take accountability.
• Team spirit and relationship-building capabilities.
• Strong communication skills for both technical and non-technical audiences.