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Auditdata is seeking a DevOps Engineer to join their software team developing enterprise solutions for audiology distribution chains. You will work in a supportive, mentorship-oriented environment focused on collaboration and skill development.
In this role, you will:
- Manage and optimize continuous integration (CI) and continuous delivery (CD) processes
- Manage release processes and their automation
- Support and monitor development environments and configurations in Microsoft Azure cloud
- Consult with internal and external customers on technical aspects of installation, sizing, scaling, and CI/CD
The team uses a modern tech stack including .NET Core, Azure Cloud, Azure DevOps, AKS, Azure SQL, Data Factory, Service Bus, and AI tools from Anthropic and OpenAI.
Auditdata is a stable, growing SaaS company with a remote-first, async-friendly culture and flat organizational structure. The global team spans Denmark, Ukraine, UK, Poland, Canada, Australia, USA, and more. They emphasize high engineering standards, personal growth, and long-term engagement.
REQUIREMENTS:
You must have 2-3 years of commercial experience with:
- Configuring, maintaining, and troubleshooting Microsoft-based production systems
- Microsoft Azure Cloud, including:
* ARM templates/Terraform writing and setup automation for resource provisioning (Azure PowerShell)
* Azure services (Azure App Service, Azure SQL, Azure Storage Account; Azure Kubernetes is a nice-to-have)
* Understanding of load balancers, DNS, virtual networks, and firewalls in cloud environments
* Setup and monitoring (performance metrics, OMS)
- Azure Active Directory basics (authentication, users and groups, roles)
- Monitoring enterprise solutions in Azure Cloud
- B.Sc. degree in Computer Science or similar
- Good spoken and written English
NICE-TO-HAVES:
- Understanding CI/CD setup for .NET projects, including managing and building CI/CD pipelines
- Hands-on use of AI coding assistants (GitHub Copilot, Claude Code, OpenAI Codex) for writing scripts, generating IaC, drafting pipeline definitions, and troubleshooting
- Basic understanding of how LLMs fit into engineering workflows, including Model Context Protocol (MCP)
- Awareness of limitations and risks of AI-generated code and configuration
KEY TRAITS:
- Strong communication skills for cross-location collaboration
- Problem-solving ability with creative thinking
- Commitment to continuous learning and staying current with tools
- Collaborative mindset in a supportive team environment
