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.