DevOps Engineers in Germany

Task: Operator development and observability

Technologies and skills: Kubernetes, Valkey-Operator, Crossplane, Backstage, OpenPortal, OTEL, Grafana Cloud, Azure DevOps, Artifactory, Flux, Alloy, Prometheus, Grafana, Loki, OCF, Copilot

What I did:

• Evaluated/developed Valkey-Operator
• Set up OpenTelemetry
• Integrated it with OpenPortal/Backstage/CrossPlane

• Architecting managed Kubernetes platforms for 150+ enterprise clients across the energy, logistics, automotive, and public sectors.
• Designed OCaaS: Kubernetes-native multi-tenant SaaS for AI assistants, with namespace-per-tenant isolation, dual-tier LLM inference, and automated tenant lifecycle management.
• Designed Chronos, Kafka as a Service on Strimzi with hybrid tenancy (shared and dedicated tiers); authored the platform RFC.
• Built multi-cluster GitOps (Flux CD, Helm, Kustomize); changes validated on ephemeral k3d clusters with Renovate + GitLab CI auto-merge.
• Architected Argus: correlated OTeI traces, logs and metrics (LGTM stack).
• Migrated secrets from HashiCorp Vault to OpenBao; built a Kyverno policy framework for RBAC automation and cross-namespace secret synchronisation.
• Built Salar: node patching and cluster upgrades with Uyuni + SaltStack.
• Built platform storage with Ceph and SeaweedFS; migrated object storage from MinIO.
• Client delivery: OTeI observability and Datadog SAML for a global cultural institute; Galera/PXC incident response for a SaaS provider.

• Manage multiple Kubernetes clusters in Production with Ceph as storage layer.
• Implemented CICD pipelines for automating deployments with Gitlab CI
• Terraform for Infrastructure provisioning.
• Claude code
• Helm charts for deploying via ArgoCD
• Implemented automated incident notification pipelines in Kubernetes to align with NIS2 mandatory 24-hour early warning disclosure rules
• Configured Azure Policy and Logging guardrails aligned with BSI IT-Grundschutz (SYS.1.3 / OPS.1.1), ensuring continuous baseline compliance across 50+ cloud workloads

Environment: Gitlab CI, IONOS Cloud, Ceph, ArgoCD, terraform, Elastic cluster, Grafana, Alert Manager & Prometheus

• Create and lead roadmap forecasting of support opportunities, including colleague training, process design and improvement, and new hire onboarding.
• Collaborate seamlessly with cross-functional teams including Professional Services, Support, Product, Sales, and Solution Engineering.
• Manage business and financial KPIs in alignment with overall business objectives.
• Industrial IT & Data Integration: Implement, configure, and integrate OT/IT systems and data flows, connecting control-layer sources (DCS, PLC, SCADA) to historians, data platforms, and enterprise systems through APIs and standard interfaces.
• AVEVA PI & Historian: Configure, maintain, and extend AVEVA PI (PI Data Archive, Asset Framework, interfaces/connectors) to capture, contextualize, and serve real-time and historical operational data.
• Alarm Management: Support and optimize alarm management systems – e.g. Honeywell Alarm Management – including alarm rationalization, classification, and the analysis of alarm performance, critical alarms, and alarm floods.
• Connectivity & Protocols: Set up and troubleshoot industrial connectivity using OPC UA and OPC A&E, including the configuration of tunnelers / wrappers to bridge OT data sources securely and reliably.
• Production Data Flow: Ensure seamless, secure, and well-structured data flow across the industrial IT landscape, transforming raw operational data into meaningful information for operations and decision-making.
• System Support & Troubleshooting: Provide ongoing support for OT/IT applications, troubleshooting issues across networks, software, and data integrations to keep systems running efficiently.
• Knowledge Management & Best Practices: Contribute to internal documentation, best practices, and troubleshooting guides, and help continuously improve how we deliver industrial IT and data solutions.

Tools & Software: Aveva PI, Salesforce, Active Directory, Microsoft Dynamics 365, Jira, Microsoft, Scrum, DevOps, Docker, CI/CD, Jenkins, GitHub.

Built and operated the entire infrastructure and observability platform for an AI agent evaluation platform on AWS/Kubernetes. Led the evolution of an AI-first cloud-native platform by building end-to-end observability, automating infrastructure and CI/CD, improving reliability and scalability, optimizing performance through data-driven engineering, and operating in an AI-native development workflow centered on rapid iteration, code review, and automation. Tech stack included Terraform, AWS, Kubernetes, Grafana, Github Actions, Python, and Cursor.

Oracle Project Management and Automation

As part of the project, the operation of an Oracle infrastructure was automated through the development and enhancement of Puppet modules and the migration of existing Bash scripts to a standardized configuration management solution.

The project aimed to standardize and automate administrative processes, improve the maintainability of the Oracle platform, and increase the efficiency and traceability of infrastructure management through the use of Infrastructure as Code.

• Analyzed and migrated existing Bash shell scripts to a Puppet-based automation solution
• Developed and enhanced Puppet modules for Oracle environments
• Automated installation, configuration, and operational processes using Infrastructure as Code
• Standardized and optimized configuration management for Oracle systems
• Created and maintained technical and operational documentation
• Planned, coordinated, and provided technical support for project implementation
• Operated and automated Oracle systems on x86-based Linux server platforms
• Tested and ensured the quality of the developed Puppet modules
• Analyzed and resolved technical issues related to automation and migration
• Worked closely with business units and infrastructure teams to implement automation requirements

Technologies used: Puppet 7/8, SLES 15, Oracle 19, Oracle Grid, SVN, Windows Server, Confluence, VS Code, Ruby, Bash, Pass

• Technical design, prioritization, and hands-on implementation of AI automation, conversational AI, voice AI, and private AI solutions.
• Translation of business requirements into system architecture, conversation/workflow logic, APIs, data flows, and production-ready AI workflows.
• Development of backend and integration components with Python/FastAPI, PostgreSQL/pgvector, Redis, REST APIs, webhooks, and background jobs.
• Design and implementation of RAG architectures with local/private LLMs, embeddings, document processing, semantic search, and controlled access to company knowledge.
• Prompt engineering for LLM and voice/conversational AI applications; iterative optimization based on real processes, system responses, and quality requirements.
• Practical work with ElevenLabs and its APIs in a voice AI project, as well as technical evaluation and integration of voice AI components.
• Deployment and operation of Docker-based systems on Linux with Nginx, CI/CD, monitoring/logging, backup/restore, and reproducible deployment processes.

• Solo MVP in 3 Months -- PRD to SRS to production: 12 Django apps + React SPA with JWT auth, delivered ahead of schedule.
• Real-Time Backend -- Django REST APIs, WebSocket channels, Celery + Redis queues, role-based access across 4 user roles.
• Multi-Tenant SaaS -- Isolated tenant provisioning with Kubernetes, Helm, and FastAPI -- subdomain live in under one minute.
• CI/CD & Infrastructure -- 5 Hetzner servers, 3 repos, branch-specific GitHub Actions auto-deploy; Dockerized full stack.
• Team Leadership -- Hired and led 3 developers across 3 countries; closed 450+ Linear tickets in 9 months.
• Full Product Scope -- Courses, quizzes, PDF certificates, user imports, real-time notifications, analytics, and subscription management.
• Live Product -- Published at iqrew.de; app complete, SaaS in final testing, market launch imminent.
• SSO & Security -- Cross-platform SSO with single-use tokens, server-to-server validation, tenant isolation, and HTTPS auto-renewal.
• Test Strategy -- 3-layer pyramid: pytest, Jest/RTL + MSW, Playwright E2E with factory fixtures and role-based auth across all roles.
• Performance Engineering -- Locust stress tests identified N+1 bottlenecks (60s timeouts); optimized to sub-250ms at 50 concurrent users, 0% failures.
• Stripe SaaS Billing -- Stripe webhook-driven upgrades, automated tenant provisioning, self-service onboarding from checkout to live tenant.

• Design, deploy, and manage scalable, highly available, and fault-tolerant systems on AWS.
• Develop and maintain Docker images for various applications and services.
• Manage Kubernetes clusters for container orchestration, ensuring efficient resource utilization and scalability.
• Monitor and troubleshoot system performance issues, ensuring optimal performance and uptime.
• Collaborate with development teams to understand application requirements and provide infrastructure solutions.
• Implement security best practices for infrastructure, applications, and data.
• Maintain and improve system documentation, procedures, and processes.
• Provide support and mentorship to team members on best practices for cloud infrastructure and containerization.
• Stay updated with the latest industry trends and best practices in cloud computing, containerization, and Dev Ops.

Clients: CARIAD, AUDI AG

• Built and deployed enterprise MLOps pipelines using Azure Machine Learning and Databricks. Reduced model release cycles by 95 percent, from four weeks to two days, through automated CI CD workflows.
• Delivered cloud native DevOps platforms for ADAS programs using Azure data services, Kubernetes, and Terraform based infrastructure provisioning.
• Designed high availability architectures with automated failover. Cut system downtime by 85 percent for mission critical energy trading platforms.
• Developed and integrated AI agents and enterprise chatbots using LangChain, AutoGPT, and GPT models. Enabled autonomous workflows and decision driven automation.
• Reduced cloud infrastructure spend by 40 percent through autoscaling strategies, spot instance usage, and policy driven resource governance across Azure and AWS.
• Partnered with Data Scientists, ML Engineers, Product Managers, and executive stakeholders to deliver large scale automotive and energy solutions.
• Implemented GitOps driven CI CD pipelines supporting automotive software delivery for over 500 engineers across distributed product teams.
• Designed and operated Kubernetes platforms on Azure AKS. Improved deployment stability and reduced rollback events by 70 percent.
• Implemented observability and monitoring stacks using Prometheus, Grafana, and Azure Monitor. Achieved 99.9 percent service availability targets.

Project: Digitalization of Warehouse Processes | Building a Data Analytics Platform.

• Built a web-based workforce allocation system that digitized daily shift planning by matching worker expertise to operational zones, replacing manual coordination with a structured workflow adopted across the site, saving supervisors time on daily planning.
• Developed a real-time operational visibility dashboard giving supervisors a live view of task throughput and outstanding workload across warehouse zones throughout the day, helping reduce overtime and idle labour costs.
• Developed a slotting optimization solution to improve warehouse picking efficiency and reduce picking time per order, working directly with operations teams from concept through production deployment.

Technologies used: Python, Django, PostgreSQL, Pandas, NumPy, HTML, Java, JavaScript, Docker, Kubernetes, AWS, Power BI, GitHub Actions CI/CD, GitOps, Claude, OpenAI

Development and further development of an internal platform for managing and providing technical resources, virtual machines, and infrastructure services. The platform supports self-service processes and covers functions that are conceptually comparable to cloud management solutions like Azure or AWS.

• Responsible involvement in the design, development, and implementation of new backend and frontend features
• Hands-on development with Java, Spring Boot, Python, and Angular
• Implementation of REST interfaces, business logic, validations, and integrations into existing system landscapes
• Further development of modern web interfaces with Angular, including connection to backend services
• Participation in architecture and design decisions within the team, especially with regard to scalability, maintainability, and clean interfaces
• Containerization and deployment of applications with Docker, Kubernetes, and Helm
• Support with CI/CD processes and deployment to Kubernetes-based environments
• Work in the environment of vSphere, Broadcom, GitLab CI/CD, ArgoCD, Maven, npm, and NuGet
• Close collaboration with developers, business teams, DevOps, and other technical stakeholders
• Analysis of technical requirements, deriving suitable solutions, and independent implementation in an agile team
• Use of GitHub Copilot to support code generation, refactoring, test case creation, and technical documentation

Methods/ tools/ technologies: Languages & frameworks: Java (21), Spring Boot (4.x), Python, Angular, Robot Framework, Kubernetes, Helm Persistence: PostgreSQL, MongoDB, Hibernate, Liquibase Architecture & communication: REST, gRPC, GraphQL, Apache Kafka, OpenAPI, Microservices, Event Driven, Domain Driven Design Cloud & infrastructure: Terraform, Docker, Rancher, Helm, Ansible Security: OAuth2, MS (Entra ID), web security, Keycloak (extensions for detailed group rights) DevOps: GitLab CI/CD, Ansible, Maven, Gradle, Grafana, Prometheus, Git, GitHub Copilot Testing & QM: JUnit, Robot Framework, automated component and integration tests, E2E tests with Playwright, Testcontainers, EasyMock Methodology & approach: Kanban, JIRA, Confluence, Clean Code

• Kubernetes: EKS management, cluster upgrades and stability improvements, Infrastructure-as-Code reviews and updates, AWS support, and cost optimization.

• Error analysis and fixes including performance optimization of the in-house developed platform API
• Change and incident management in day-to-day operations
• Responsible for compliance with security and compliance requirements
• Vendor management for software development and maintenance
• Planning and execution of migration of legacy services to a cloud native platform

Role in the project: project staff, implementation team

Used skills: requirements analysis, IT service and application management, IT operations, error analysis and performance optimization, software maintenance and lifecycle management

Project environment: Cloud Native Platform (Kubernetes, Crossplane, AWS, ArgoCD, Grafana)