Azure Cloud Engineer

Accountabilities:

• Administer Azure cloud infrastructure across dev, QA, staging, and production environments, maintaining services like Container Apps, Static Web Apps, PostgreSQL, Service Bus, Azure Arc, and SignalR.

• Develop and maintain modular Infrastructure as Code using Terraform, managing state files, workspaces, variable structures, resource tagging, and drift remediation.

• Build, safeguard, and troubleshoot automated CI/CD deployment workflows in GitHub Actions, implementing release gates, approval mechanisms, secret protection, and rollback procedures.

• Monitor operational health, latency, quotas, token usage, and costs for Azure AI services, including Azure AI Foundry, Speech-to-Text workloads, and LLM integrations.

• Implement observability, dashboards, and actionable alerts using Azure Monitor, Log Analytics, and Application Insights while establishing clear SLIs and SLOs.

• Drive incident response, triage, and root-cause analysis across deployments, maintaining operational runbooks, disaster recovery strategies, and security compliance standards (e.g., SOC 2, ISO 27001).

Requirements:

• 5+ years of hands-on experience operating production-grade enterprise workloads within Microsoft Azure environments.

• Deep proficiency with Infrastructure as Code using Terraform, alongside CI/CD pipeline automation through GitHub Actions.

• Strong background in containerized applications (Azure Container Apps), managed relational databases (Azure PostgreSQL), and cloud networking/identity protocols (DNS, RBAC, Key Vault, Managed Identities).

• Demonstrated experience setting up enterprise observability using Azure Monitor, Log Analytics, and Application Insights.

• Solid scripting skills in Bash, PowerShell, or Python for operational automation, health checks, and troubleshooting.

• Excellent cross-functional communication and documentation skills, with preferred exposure to AI service operations (Azure OpenAI/AI Foundry), message queues (Service Bus), or FinOps cost optimization.

Benefits:

• Competitive salary package commensurate with experience and technical expertise.

• 100% remote work model offering schedule autonomy and flexibility.

• Comprehensive opportunities for career advancement, skill expansion, and professional certifications.

• Direct hands-on experience operating production AI systems and LLM integrations at enterprise scale.

• Diverse, collaborative international environment within a forward-thinking technology team.