Summary
✨ AI‑Generated
An enterprise software organization is seeking an Azure Cloud Engineer to take operational responsibility for the reliability, security, scalability, and performance of cloud-hosted SaaS environments. You will automate infrastructure with Terraform, maintain CI/CD pipelines, operate containerized microservices and managed databases, and implement monitoring, high-availability standards, and cloud cost controls. Familiarity with cloud-based AI and speech-processing services is beneficial. The role operates within a remote, outcome-driven engineering culture and is intended for candidates based in the Netherlands.
Highlights
Remote, outcome-driven working culture with substantial operational ownership over cloud environments. Work closely with engineering teams on infrastructure automation, reliable deployments, cloud security, cost governance, and emerging AI services across development, staging, and production environments.
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 Netherlands.
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.
How Jobgether Works
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements.
Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company.
The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer.
This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR).
You may exercise your rights (access, rectification, erasure, objection) at any time.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information.
These tools assist our recruitment team but do not replace human judgment.
Final hiring decisions are ultimately made by humans.
If you would like more information about how your data is processed, please contact us.
