About this role
**Company:** The team
**Job Location:** Remote Initially from Chennai | Abu Dhabi, UAE (Potential Onsite Relocation after 2 months if required)
**Experience:** 6+ Years (Including 3+ Years in Azure Production Environments)
**Reporting To:** AI & Data Manager
About the Opportunity
The team is looking for an experienced **Senior DevOps Engineer – Azure Platform & Infrastructure as Code (IaC)** to manage, secure, automate, and optimise an enterprise-grade Azure Data & AI platform.
The platform operates within a **hub-spoke Azure landing zone with private networking**, supporting enterprise AI agents, web applications, APIs, data pipelines, and cloud services. Several solutions have been developed by external delivery partners and require technical assessment, standardisation, and deployment automation.
The successful candidate will take ownership of Azure infrastructure provisioning, CI/CD automation, environment management, cloud security, and production deployment practices.
This is a **hands-on senior engineering role** requiring strong expertise in Azure DevOps, Terraform, Bicep, Azure networking, cloud security, and automated application deployments.
We are particularly interested in candidates who have experience **reviewing existing Azure environments, improving infrastructure architecture, and replacing manual deployment processes with secure, automated CI/CD pipelines.**
Work Arrangement & Relocation
- **Initial Engagement:** Remote for the first 2 months.
- **Performance Evaluation:** Technical capabilities, infrastructure ownership, automation delivery, and problem-solving skills will be assessed during the initial engagement.
- **Potential Relocation:** Following successful evaluation, the role may require relocation to Abu Dhabi, UAE, for an onsite or hybrid engagement.
- **Contract Extension:** Subject to project requirements, performance, and mutual agreement.
**Important:** Candidates must be willing to relocate to Abu Dhabi after the initial remote engagement if required. Please apply only if you are comfortable with this arrangement.
Key Responsibilities1. Azure Infrastructure & Platform Engineering
- Manage and optimise enterprise Azure infrastructure within a hub-spoke landing zone architecture.
- Review existing cloud infrastructure, deployed resources, networking, security configurations, and operational practices.
- Design scalable, secure, and reusable Azure infrastructure patterns.
- Manage development, UAT, production, and temporary staging environments.
- Establish infrastructure standards, resource organisation, naming conventions, tagging, and governance policies.
2. Infrastructure as Code (Terraform & Bicep)
- Design, develop, and maintain Infrastructure as Code using **Terraform and Azure Bicep**.
- Create reusable Terraform modules and Bicep templates for Azure infrastructure provisioning.
- Implement secure remote state management, configuration management, and environment-specific deployments.
- Introduce infrastructure validation, automated testing, and policy-as-code controls.
- Migrate manually configured Azure resources into repeatable, version-controlled infrastructure deployments.
- Ensure infrastructure changes follow approved review and release processes.
3. Azure DevOps & CI/CD Automation
- Design and implement **multi-stage Azure DevOps YAML pipelines** for build, testing, and deployment.
- Create reusable pipeline templates for enterprise applications, APIs, and AI workloads.
- Configure Azure DevOps environments, service connections, approvals, and deployment gates.
- Implement branch protection, pull request reviews, and controlled production releases.
- Automate deployments across development, UAT, and production environments.
- Establish rollback procedures, release traceability, and deployment documentation.
- Eliminate manual production deployments wherever practical.
4. Application & AI Workload Deployment
- Deploy and manage enterprise applications using Azure App Service, Azure Functions, Logic Apps Standard, and Azure Container Apps.
- Develop reusable deployment blueprints for web applications, APIs, AI agents, databases, and storage.
- Support automated deployment of AI solutions using Azure AI Foundry, Azure OpenAI, and Azure AI Search.
- Collaborate with AI and Data Engineering teams to automate AI agent and data pipeline deployments.
- Manage application configuration, secrets, environment variables, and deployment dependencies.
- Troubleshoot deployment failures, application hosting issues, and infrastructure-related incidents.
5. Azure Networking, Identity & Security
- Manage Azure hub-spoke networking, VNet integration, private endpoints, and private DNS configurations.
- Implement secure connectivity between applications, AI services, databases, and enterprise systems.
- Configure Microsoft Entra ID, Azure RBAC, Managed Identities, and least-privilege access controls.
- Manage application secrets, certificates, and credentials using Azure Key Vault.
- Implement controlled access for external delivery partners and technical teams.
- Apply Azure Policy and cloud security best practices to support compliance and governance.
- Review existing access permissions and identify security risks or excessive privileges.
6. Monitoring, Reliability & Cost Optimisation
- Implement monitoring and alerting using Azure Monitor, Log Analytics, and Application Insights.
- Develop KQL queries, dashboards, and operational alerts for cloud services.
- Establish logging, health monitoring, and incident troubleshooting procedures.
- Create operational runbooks for deployments, incidents, recovery, and platform maintenance.
- Implement resource tagging, cost visibility, and Azure consumption controls.
- Identify opportunities to optimise compute, storage, networking, and application hosting costs.
7. Technical Leadership & Collaboration
- Work closely with the AI & Data Manager, internal engineering