Azure Cloud Engineer

Jobgether SRL; Deutschland; Remote; EUR 90,000 - 120,000; Full time

Benefits offered by this job

100% remote work

Career development

International team

Job summary

Lever, Inc. in Germany seeks an Azure Cloud Engineer to own the reliability, security, and performance of Azure-hosted workloads across dev, QA, staging, and production. You will automate infrastructure with Terraform, and build CI/CD pipelines via GitHub Actions, working with Container Apps, PostgreSQL, Service Bus, and AI services.

In a remote, outcome-driven culture, you will implement observability, cost governance, and high-availability standards for enterprise SaaS globally.

Qualifications

• 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 exposure to AI service operations (Azure OpenAI/AI Foundry) and FinOps cost optimization.

Responsibilities

• 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).

Skills

Terraform IaC

GitHub Actions

Bash

PowerShell

Python

DNS & RBAC

Azure OpenAI/AI Foundry

Incident response

Tools

Azure Container Apps

Azure PostgreSQL

Service Bus

Azure Arc

SignalR

Terraform state

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Azure Cloud Engineer based in Germany.

As a CloudOps engineer supporting an enterprise SaaS portfolio rebuilding vertical software with AI, you will hold complete operational responsibility for the reliability, security, scalability, and performance of Azure-hosted environments. Operating in an outcome-driven, remote culture, you will partner directly with forward-deployed engineering teams to automate infrastructure using Terraform and maintain CI/CD pipelines via GitHub Actions. Your scope covers everything from containerized microservices and managed databases to cutting-edge Azure AI Foundry and Speech-to-Text services across dev, staging, and production tiers. By establishing robust monitoring, finops cost-governance, and high-availability standards, your contributions will directly ensure seamless uptime and rapid production deployments for software running mission-critical operations worldwide.

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.