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tekkminds

Senior Cloud Software Engineer, Backend – AI

tekkminds

. Design and develop cloud-native applications with Java/Kotlin and Spring Boot .

Posted 10/6/2026full-timeMunich • GermanySeniorWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in designing and developing cloud-native applications using Java/Kotlin and Spring Boot, with a strong focus on REST API implementation and MLOps for AI components. Proficient in containerization and orchestration with Docker and Kubernetes, alongside experience in backend modernization and technical consulting for enterprise clients.

Highest-signal resume keywords
Java/Kotlin Backend DevelopmentSpring BootDocker and KubernetesCI/CD Pipeline OptimizationMLOps for AI Components

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
JavaKotlinSpring BootREST API DevelopmentDockerKubernetesCI/CD ToolsLangChainVector DatabasesMCP Integration
Soft Skills
Strong Communication SkillsArchitectural ThinkingWillingness to LearnPragmatic Approach
Tools & Technologies
AWSAzureGCPGitLabJenkinsGitHub ActionsArgoCDFlux
Industry Keywords
Cloud-Native ApplicationsAI IntegrationRAG SystemsAgent-Based ArchitecturesEmbedding Technologies

Tech Stack

Tools & technologies
AWSAzureCloudDockerFluxGoogle Cloud PlatformJavaJenkinsKotlinKubernetesOpenShiftPythonSpringSpring BootSpringBoot

About the role

Key responsibilities & impact
  • Design and develop cloud-native applications with Java/Kotlin and Spring Boot
  • Design and implement REST APIs for enterprise systems
  • Containerize and orchestrate applications using Docker and Kubernetes/OpenShift
  • Build and optimize CI/CD pipelines
  • Migrate and modernize existing backend systems
  • Develop RAG (Retrieval-Augmented Generation) systems with LangChain/LangChain4J
  • Implement MCP servers to integrate existing APIs with LLMs
  • Build agent-based architectures and agent-to-agent communication
  • Integrate vector databases and embedding technologies
  • Deploy and monitor AI components in the cloud (MLOps)
  • Provide technical consulting to enterprise clients on AI integration projects
  • Make architectural decisions at the intersection of backend and AI
  • Further develop internal standards and best practices

Requirements

What you’ll need
  • 5+ years of experience in backend development with Java/Kotlin
  • Strong knowledge of Spring Boot or Jakarta EE
  • Hands-on 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 through a personal project, proof of concept, or production deployment
  • Understanding of RAG concepts or the motivation to learn them quickly
  • Business-fluent German
  • Fluent English
  • Python knowledge for ML/AI components (nice to have)
  • Experience with LangChain, LlamaIndex, or LangChain4J (nice to have)
  • Knowledge of vector databases (Pinecone, Weaviate, Qdrant, ChromaDB) (nice to have)
  • Experience with the Model Context Protocol (MCP) or agent frameworks (nice to have)
  • Experience with prompt engineering or model fine-tuning (nice to have)
  • GitOps experience with ArgoCD or Flux (nice to have)
  • Strong communication skills in direct client interactions
  • Architectural thinking
  • Willingness to learn about rapidly evolving AI technologies
  • Pragmatic approach to work

Benefits

Comp & perks
  • Paid certifications—AWS, Azure, GCP, and Kubernetes: we cover the costs
  • Generous professional development budget for AI courses and conferences
  • Access to leading AI communities and meetups (speaking opportunities welcome)
  • Work with modern AI frameworks (Spring AI, Embabel, LangChain(4J), ADK, Strands, AutoGen, or similar)
  • Challenging enterprise projects with renowned clients
  • Freedom to choose your tools and hardware—select your preferred laptop and phone
  • Innovation lab for proof-of-concepts
  • Modern office with excellent public transport connections
  • Agile teams with short decision-making processes
  • Freedom to drive your own technical initiatives
  • Regular internal tech talks on AI trends
  • Time during working hours to write blogs and technical articles
  • Close team collaboration—we learn from one another