Key skills
AWSAzureCloudDockerFluxGoogle Cloud PlatformJavaJenkinsKotlinKubernetesOpenShiftPythonSpringSpring BootSpringBootAIMLRAGLangChainLlamaIndexMLOpsQdrantPineconeWeaviateGCPGoogle CloudGitHub ActionsArgoCDGitHubGitLabGitOpsAgileCI/CDCommunicationCollaborationNegotiation
About this role
Role Overview
- Backend development (50%)
- Design and develop cloud-native applications using Java/Kotlin and Spring Boot
- Design and implement REST APIs for enterprise systems
- Containerization and orchestration with Docker and Kubernetes/OpenShift
- Build and optimize CI/CD pipelines
- Migration and modernization of existing backend systems
- AI integration (50%)
- Develop RAG systems (Retrieval-Augmented Generation) with LangChain/LangChain4J
- Implement MCP servers for integrating LLMs with existing APIs
- Build agent-based architectures and enable agent-to-agent communication
- Integrate vector databases and embedding technologies
- MLOps: deployment and monitoring of AI components in the cloud
- Technical consulting for enterprise customers on AI integration projects
- Make architecture decisions at the backend/AI interface
- Further develop our internal standards and best practices
Requirements
- 5+ years of experience in backend development with Java/Kotlin
- Strong knowledge of Spring Boot or Jakarta EE
- Practical experience with Kubernetes and at least one cloud platform (AWS/Azure/GCP)
- Hands-on experience with Docker and CI/CD tools (GitLab, Jenkins, GitHub Actions)
- Practical experience with LLMs — whether a personal project, proof of concept, or production deployment
- Understanding of RAG concepts or the motivation to learn them quickly
- German: business fluent (negotiation level)
- English: fluent
- Nice-to-have: Python skills for ML/AI components
- Experience with LangChain, LlamaIndex, LangChain4J
- Knowledge of vector databases (Pinecone, Weaviate, Qdrant, ChromaDB)
- Familiarity with Model Context Protocol (MCP) or agent frameworks
- Experience with prompt engineering or model fine-tuning
- GitOps experience with ArgoCD or Flux
Tech Stack
- AWS
- Azure
- Cloud
- Docker
- Flux
- Google Cloud Platform
- Java
- Jenkins
- Kotlin
- Kubernetes
- OpenShift
- Python
- Spring
- Spring Boot
- SpringBoot
Benefits
- Paid certifications – AWS, Azure, GCP, Kubernetes: we cover the costs
- Generous learning & development budget for courses and conferences in the AI field
- Access to leading AI communities and meetups (speakers welcome)
- Freedom to choose tools and hardware – laptop and phone of your choice
- Innovation Lab for proofs-of-concept
- Modern, well-equipped office with excellent transport connections
- Agile teams with short decision-making paths
- Freedom to shape your own technical initiatives
- Regular internal tech talks on AI trends
- Time allocated during work hours for blogs and technical articles
- Close collaboration within the team – we learn from each other