Azure DevOps Engineer
Summary
Long-term contract role building and running a Generative AI platform on Microsoft Azure: provisioning infrastructure with Terraform and Helm, automating GitLab CI/CD pipelines, operating Kubernetes workloads (including Langfuse), and monitoring RAG and Agentic AI services in production with Prometheus, Grafana, and Azure Monitor. Fluent German and English required.
Employment Type: Long-term contract with further extensions
Language: Fluent German and English
Overview:
We are looking for an experienced Azure DevOps Engineer specializing in GenAI Platform Engineering and LLMOps to develop, operate, and continuously improve a modern Generative AI platform built on Microsoft Azure.
In this role, you will be responsible for managing Azure cloud infrastructure, automating deployment pipelines, and ensuring the reliable, secure, and scalable operation of GenAI applications. You will work with technologies such as Azure OpenAI, Azure AI Foundry, Azure AI Search, Kubernetes, Terraform, and GitLab CI/CD to support the deployment and operation of RAG and Agentic AI solutions in production environments.
The ideal candidate combines strong Azure Cloud and DevOps expertise with practical experience in GenAI platforms, infrastructure automation, monitoring, and production operations.
Roles and Responsibilities:
- Develop, operate, and continuously improve a modern GenAI platform based on Microsoft Azure.
- Provision and manage infrastructure as code using Terraform, Helm Charts, Git, and GitLab.
- Automate build, test, and release processes for GenAI applications to ensure reliable deployments across development, testing, and production environments.
- Operate and further develop Kubernetes-based applications and services, including tools such as Langfuse.
- Implement and optimize monitoring, logging, and alerting solutions using Prometheus, Grafana, and Azure Monitor.
- Monitor system performance, availability, and logs while proactively identifying and resolving operational issues.
- Develop technical concepts and architectural solutions to support new requirements and continuously optimize the GenAI platform.
- Implement and enhance authorization checks, logging, monitoring, and routing logic.
- Ensure compliance with enterprise-wide standards, IT security requirements, and relevant regulatory guidelines.
- Collaborate with IT security, domain architecture, development teams, and other stakeholders.
- Support client application teams with technical guidance, integrations, onboarding, and troubleshooting during production operations.
Requirements:
- Strong hands-on experience with Microsoft Azure cloud services and infrastructure management.
- Solid experience with DevOps toolchains and automation, particularly Git, GitLab CI/CD, Docker, and Terraform.
- Practical experience with Kubernetes-based applications and infrastructure automation.
- Experience with monitoring, logging, and alerting tools such as Prometheus, Grafana, and Azure Monitor.
- Project experience with Generative AI technologies, particularly Retrieval-Augmented Generation (RAG) and/or Agentic AI.
Nice to Have:
- Experience optimizing and operating GenAI solutions in production environments.
- Practical experience with LLMOps and the lifecycle management of LLM-based applications.
- Knowledge of authentication and authorization mechanisms, particularly Microsoft Entra ID, Role-Based Access Control (RBAC), and OAuth.
- Programming experience in Python and/or Java.
- Experience developing technical concepts and architectural proposals in collaboration with IT security and domain architecture teams.