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 Pune
Work model: Hybrid working (3 days / week in office)
Work hours: CET Time zone (9 hours)
Goals and deliverables
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 GCP/Azure CloudFormation and GCP/Azure CDK ensuring efficient
repeatable and consistent infrastructure deployments - including complex multi-service
AI and Data platforms
Implement and manage security practices such as Identity and Access Management
network security and encryption to ensure data protection and compliance with industry
standards and regulations
Design provision and manage Azure AI and Data platform components via IAC to
support AI exploration discovery experimentation and production deployment Key
services include Microsoft Fabric (Lakehouse Realtime analytics data science and AI
workload Azure OpenAI service Azure MLL/AI studio etc
Partner with data science AI engineering MLOps and data teams to design and deliver
governed AI Landing zones and environments that accelerate model development
agentic systems implement backup disaster recovery and failover solutions for high
availability and business continuity
Leverage agentic AI Tools GitHub copilot Azure AI Agents and custom agent workflows
as well as AI-assisted engineering practices to significantly boost productively in
writing/reviewing Terraform/Bicep code infrastructure troubleshooting documentation
generation cost optimization policy-as-code and proactive platform improvement.
Create and maintain comprehensive documentation of infrastructure architecture
configuration and troubleshooting steps and share knowledge with team members
Close collaboration with multi-cloud enterprise architect DevOps solution architect
Cloud Operations Manager to ensure quick MVP prior to pushing into production
Keep up to date with new GCP/Azure services features and best practices - Especially
in the AI Data Fabric and MLOps space providing recommendations for process and
architecture improvements
Education and experience

Bachelors degree in information technology Computer Science Business
Administration or related field. Masters degree or relevant certifications would be a plus.
Minimum of 5 years of experience in cloud engineering cloud architecture or
infrastructure role ideally with exposure to data or AI/ML workloads.
Proven experience with GCP/Azure services including Virtual Machines / Compute
Engine Blob Storage / Azure Data Lake Storage / Cloud Storage Azure SQL Database /
Cosmos DB or Cloud SQL Azure Functions / Cloud Functions Virtual Network / VPC
Microsoft Entra ID / IAM and RBAC and native monitoring tools. Hands-on experience
deploying and managing Azure AI and analytics services (Microsoft Fabric Azure
OpenAI Service Azure Machine Learning / Azure AI Studio Azure AI Search and
related components) via Infrastructure-as-Code (Terraform) is highly desirable
Hands-on experience with Infrastructure-as-Code (IaC) tools such as Terraform
GCP/Azure CloudFormation or GCP/Azure CDK Bicep and ARM templates for Azure
(and equivalent tools for GCP). Ability to codify complex governed AI/data platforms is a
significant advantage.
Strong scripting skills in Python Bash or PowerShell for automation tasks
Familiarity with CI/CD tools (eg: Gitlab CI/CD Jenkins) and experience integrating them
with GCP/Azure
Knowledge of networking fundamentals and experience with GCP/Azure VPC security
groups VPN and routing and secure private connectivity patterns for AI services (e.g.
private access to OpenAI Fabric and storage).
Proficiency in monitoring and logging tools such as native cloud tools or third-party tools
like Datadog and Splunk
Familiarity with or hands-on use of agentic AI systems AI coding assistants or multi-
agent frameworks to augment infrastructure-as-code development operational
automation and cloud engineering workflows is a distinct plus. Examples include GitHub
Copilot (or similar) for Terraform/Bicep custom agents for infra tasks Azure AI Agent
Service or equivalent.

Required Skills:

Azure Cloudagentic AIAi