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# Platform Engineer - Agentic AI Platform

- **Company:** UNIQA Insurance Group AG
- **Location:** Austria (Remote available)
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Application Performance Management, Microsoft Azure, Continuous Integration, Github, Identity and Access Management, Role-Based Access Control, Azure Machine Learning, Management of Software Versions, Data Logging, Software Distribution, Cloud Monitoring, Terraform, Splunk, Dynatrace
- **Published:** June 30, 2026
- **Apply:** https://careers.uniqagroup.com/job/Wien-Platform-Engineer-Agentic-AI-Platform-%28wmd%29/1409423033/

## About the Role

* Azure Platform Engineering Erfahrung (Networking, Subscriptions, Landing Zones, Security)
 * Erfahrung mit Azure AI Foundry / Azure OpenAI / Azure AI Services oder vergleichbaren AI-Plattformen im Productiveinsatz
 * Infrastructure-as-Code Know-how (bevorzugt Terraform) samt reproduzierbarer Deployments
 * Erfahrung mit CI/CD (Azure DevOps oder GitHub Actions)
 * Fundiertes Wissen in IAM, Azure RBAC, Managed Identities, Entra ID, Secret Management und sicherer Konfiguration
 * Starke Kenntnisse in Observability sowie AI Governance (Zugriff, Quotas, Responsible AI, Auditability)
 * Sehr gute Deutsch- und Englischkenntnisse

Nice to have

 * Erfahrung mit MCP-Infrastruktur oder vergleichbaren AI-Integrationsruntimes
 * Betrieb von AI-Workloads in Scale (Endpoint-, Quota- und Cost-Management)
 * Erfahrung mit containerisierten Plattformen, idealerweise AKS
 * Know-how in Monitoring-Tools (z. B. Dynatrace, Splunk, OpenTelemetry, Azure Monitor, Application Insights)
 * Kenntnisse in FinOps für AI-Consumption
 * Erfahrung mit Zero-Trust Networking für AI-Services und plattformübergreifenden Release-Prozessen

## Description

* Aufbau, Betrieb und Weiterentwicklung der Agentic AI Platform auf Azure inkl. Infrastruktur, Networking, Access Control, Secrets und Zertifikate
 * Deployment & Betrieb von Azure AI Foundry (Model Endpoints, AI Services, Workspaces) inkl. vollständigem Model Lifecycle (Rollout, Versionierung, Testing, Rollback)
 * Umsetzung von Infrastructure-as-Code (v. a. Terraform) sowie CI/CD-Pipelines für reproduzierbare, auditierbare Plattform-Releases
 * Sicherstellung von Observability (Logging, Metrics, Tracing, Performance, Token-Nutzung, Kosten) sowie laufende Optimierung, Troubleshooting und Upgrades
 * Implementierung von Security & Governance (Guardrails, Policies, IAM, Quotas, Responsible AI, Auditability) inkl. sicherer Connectivity (Private Endpoints, VNET, Isolation)
 * Betrieb von MCP-Infrastruktur sowie FinOps (Consumption, Budget, Kostenoptimierung), Capacity- & Quota-Management und konsistenter Plattformbetrieb gruppenweit


## Related Videos

- [Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure](https://www.wearedevelopers.com/videos/1532-agentic-ai-from-theory-to-practice-developing-multi-agent-ai-systems-on-azure)
- [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next)
- [Our journey with Spring Boot in a microservice architecture](https://www.wearedevelopers.com/videos/511-our-journey-with-spring-boot-in-a-microservice-architecture)
- [Infrastructure as Code: The Developer's Secret Weapon](https://www.wearedevelopers.com/videos/1221-infrastructure-as-code-the-developer-s-secret-weapon)
- [From AI Assistance to Agentic Systems: Scaling Sovereign AI in Banking](https://www.wearedevelopers.com/videos/100070-from-ai-assistance-to-agentic-systems-scaling-sovereign-ai-in-banking)
- [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models)

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