3+ years' experience in cloud engineering, platform, DevOps or SRE roles, with exposure to AI platform enablement
Strong hands-on experience with cloud platforms (ideally Microsoft Azure), including networking, identity, storage and security
Practical experience with Kubernetes and containerised workloads (AKS preferred)
Solid understanding of AI/ML workloads, including training vs. inference, scaling behaviour and resource requirements
Requirements:
Design AI cloud solution architectures for infrastructure, data, security and integration patterns for AI workloads
Define reusable templates, standards and architectures for efficient cloud-based deployment of AI, ML and GenAI workloads
Collaborate with Cloud Platform, SRE, Architecture and Engineering teams to ensure scalable and reliable AI services
Enhance monitoring, incident response, and ensure compliance, data protection, and best practices
Job description
What is Jedox?
At Jedox, we help businesses plan for a better future. Our Enterprise Performance Management (EPM) software empowers finance, sales, and other departments to budget, forecast, and analyze data—all in one intuitive platform. We’re on a mission to turn complex planning into #Superplännen: that amazing moment when everything goes exactly as you envisioned it.
Your Responsibilities
As an AI & Automation Cloud Infrastructure Engineer, you will shape and constantly develop Jedox's in-house AI cloud platform, allowing expandable, protected, and automated AI, ML, and GenAI workloads. This highly technical role involves designing, building and operating robust cloud infrastructures, defining reusable standards and ensuring operational excellence in production.
By working closely with the Cloud Platform, SRE, Architecture and Engineering teams, you will combine your expertise in cloud engineering with your knowledge of AI and automation to deliver reliable, cost-efficient and cloud-native AI services that will drive Jedox’s innovation forward.
Design AI cloud solution architectures: Design and develop strong architectures for infrastructure, data, security and integration patterns for AI workloads.
Enable AI, ML and GenAI workloads: Define reusable templates, standards and architectures for efficient cloud-based deployment.
Collaborate across teams: Work closely with the Cloud Platform, SRE, Architecture and Engineering teams to ensure scalable and reliable AI services.
Implement GitOps workflows: Promote controlled environment PR-based processes for models, services and infrastructure.
Support MLOps lifecycle: Contribute to model deployment, promotion, rollback and operational support.
Ensure production readiness: Design for scalability, performance and high availability in production environments, with the aim of ensuring maximum efficiency and reliability.
Strengthen observability, reliability, and security: Enhance monitoring, incident response, and ensure compliance, data protection, and best practices.
Improve observability, reliability and security: Improve Ensure compliance, data protection and best practices by enhancing monitoring and incident response.
Enable platform evolution and provide expert advice: Contribute to AI platform roadmaps and serve as a subject-matter expert for AI cloud technologies.
Your Profile
3+ years' experience in cloud engineering, platform, DevOps or SRE roles, with exposure to AI platform enablement.
Strong hands-on experience with cloud platforms (ideally Microsoft Azure), including networking, identity, storage and security.
Practical experience with Kubernetes and containerised workloads (AKS preferred)
Solid understanding of AI/ML workloads, including training vs. inference, scaling behaviour and resource requirements
Hands-on experience with automation, GitOps and MLOps concepts (e.g. CI/CD, model lifecycle, Argo CD and Helm)
Experience with observability, reliability and cost-aware cloud operations (e.g. monitoring stacks and FinOps basics)
Strong software engineering mindset, with the ability to build maintainable automation, tools or services
Highly motivated to continuously learn and develop skills.
Excellent written and verbal English communication skills with strong attention to detail.
Location: We are ideally looking for a candidate based near one of our office locations in Frankfurt or Freiburg. But if you are located anywhere in Germany and willing to travel for team meetings, we would also be delighted to hear from you.
Transparency Note: Use of Artificial Intelligence
As a tech-driven company, Jedox uses modern technologies — including AI — to continuously improve our processes. In recruiting, AI may support us in screening and structuring applications. It does not replace human judgment, but helps us reduce bias and ensure a consistent candidate experience. Your application is always reviewed by real people.
If you would like to learn more about the process, please visit the website of our partner Hi People. Here you will find information about the data protection guidelines as well as the most recent security checks. This gives you complete clarity on how your data is protected and processed. Of course, you can also contact us at any time if you have any questions.
