Kubernetes engineer Jobs in Köln

About us

neuland.ai is an innovative German company with extensive expertise in AI and digital transformation. Based on our broad experience from numerous AI projects, we have developed the neuland.ai HUB – a trusted AI platform “Made in Germany.” With our proprietary and patent-pending technologies, the neuland.ai HUB is more than just a platform: it is a secure environment for sovereign, context-aware AI usage across business, government, and academia.

Our Commitment to Diversity:
At neuland.ai, we thrive on diverse perspectives. We evaluate you based on your skills and passion – regardless of background, gender, age, religion, or identity. To further strengthen the diversity of our team, candidates from underrepresented groups will be given preference if equally qualified. Don’t hesitate to apply, even if you don’t (yet) meet 100% of the requirements!

Purpose of the role

We’re looking for an experienced DevOps / Platform Engineer to help design, build, and operate the infrastructure behind our AI-powered platform. If you enjoy building reliable systems, automating everything, and enabling teams to ship quickly and safely — we’d love to talk.

Your mission

• Build, maintain, and evolve our cloud infrastructure across modern platforms (primarily Azure)
• Operate and scale Kubernetes clusters running production workloads
• Manage containerized services using Docker, Kubernetes, and Helm
• Design and maintain Infrastructure as Code with Terraform
• Build and operate CI/CD pipelines using GitHub Actions Plan and execute automated releases, deployments, and rollback strategies
• Support customer environments, including onboarding, updates, and migrations into client Azure tenants
• Implement strong infrastructure security, secrets management, and access control
• Improve monitoring, logging, and alerting to ensure full system observability
• Operate AI infrastructure components, including AI gateways (e.g., LiteLLM) and model-serving infrastructure
• Work closely with Frontend, Backend, and AI teams to optimize deployments and platform reliability
• Drive improvements in performance, reliability, cost efficiency, and automation
• Maintain clear and useful technical documentation for infrastructure, deployments, and operational processes
• Communicate infrastructure decisions clearly across engineering teams and stakeholders
• Move fast and pragmatically for non-critical tasks, while being careful, structured, and reliability-focused for production systems

Your profile

• Several years of experience as a DevOps, Platform, or Cloud Engineer running production systems
• Strong experience operating Kubernetes environments
• Deep understanding of Linux systems, networking, and OS-level performance and security
• Strong cloud experience (Azure or another major cloud provider)
• Experience with Terraform and Infrastructure as Code
• Experience designing and operating CI/CD pipelines (GitHub Actions, Azure DevOps, etc.)
• Experience with Docker, containerized workloads, and microservice platforms
• Strong understanding of security best practices, secrets management, and compliance (e.g., GDPR)
• Experience with Prometheus, Grafana, and centralized logging systems
• Strong scripting skills (Bash / Python) and confidence working with YAML-heavy environments

• Experience migrating infrastructure between cloud providers
• Exposure to AI/ML infrastructure, GPU workloads, or MLOps pipelines
• Experience operating AI gateways such as LiteLLM or similar model routing layers
• Experience supporting enterprise or multi-tenant SaaS environments
• Experience on OpenShift

• Build and scale modern AI infrastructure used in production
• Work with Kubernetes, cloud-native platforms, OpenShift and AI workloads
• A collaborative and ownership-driven engineering culture
• Remote-first work and flexible hours
• Training, certifications, and the opportunity to shape our AIOps vision
• Virtual Stock Option Plan (VSOP)

What we offer

• Build and scale modern AI infrastructure used in production
• Work with Kubernetes, cloud-native platforms, OpenShift and AI workloads
• A collaborative and ownership-driven engineering culture
• Remote-first work and flexible hours
• Training, certifications, and the opportunity to shape our AIOps vision
• Virtual Stock Option Plan (VSOP)