Service Mesh Experts in Germany

• Worked as freelance Senior DevOps Consultant on-site for IBM at a European Union Agency, operating in a highly secure, air-gapped environment managing classified systems.
• Led automation and DevOps initiatives for a large-scale OpenShift platform (>400 nodes), driving deployment efficiency, GitOps adoption, and operational automation using Ansible, Python, and Bash while ensuring compliance with security requirements.
• Spearheaded automation of release and deployment workflows in a private cloud environment hosting 400+ OpenShift nodes, significantly improving deployment speed and reliability.
• Migrated existing playbooks, roles, and templates from Ansible Tower to Ansible Automation Platform (AAP), ensuring full compliance with fully-qualified collection names (FQCN) and preparing custom Execution Environments (EE) for containerized automation.
• Implemented GitOps Agent for AAP Controller Configuration as Code, enabling automated synchronization (CRUD) of Ansible Controller objects based on repository-stored configuration definitions using GitHub webhooks.
• Designed and automated complex multi-step operational workflows including environment cleanup, Helix cluster component re-creation, Kafka topic management, and OpenShift object lifecycle management across ~100 environments.
• Achieved a reduction of multi-day manual operations to under a few hours through automation improvements spanning multiple AAP clusters and OpenShift environments.
• Integrated Ansible Automation Platform with Thycotic (Delinea) Secret Server via lookup plugin to enhance secure credential management in automated processes.
• Managed deployment tasks, platform troubleshooting, and Istio network configurations while adhering to stringent EU PSC security and compliance standards.
• Collaborated with infrastructure and application teams to refine deployment procedures, develop naming conventions, and continuously improve automation coverage in an air-gapped, classified environment.

• Fully on-premises LLM document-examination platform for a compliance-critical banking domain: agentic LangGraph pipeline with deterministic verification, every AI judgment structured and source-anchored; ~960 automated tests, zero data egress
• GPU throughput engineering (quantized serving, speculative decoding, prefix caching): 9.5x extraction speed-up, 500+ multi-document case files per day on a single A100
• AI-native EDI/EDIFACT integration platform (~116k LOC Java 25 / Spring Boot 4, 1,900+ tests): LLM-drafted partner mappings machine-verified before go-live (DFDL conformance, field-coverage checks, dry runs), ~99.5% byte match on real customer files — replacing weeks of manual mapping per partner

• Development and introduction of operations processes
• Preparation of complete documentation packages (including incident management and operations support) to meet compliance requirements
• Introduction of a workshop on IaC (Infrastructure as Code)
• Technical consulting for the project security concept (ISMS)
• Installation and operation of Kubernetes clusters on AWS, on-prem, and Azure
• Hybrid cloud architecture design (on-prem, Hetzner, AWS)
• Analysis and troubleshooting of incidents and system outages
• Network adjustments for firewall rules, gateways, OpenVPN settings, and IPsec tunnels (pfSense)
• Technical consulting on Bitbucket, Jenkins, and GitLab CI/CD pipelines
• Consulting on Ansible deployments and infrastructure automation
• Consulting on building a scalable system in the cloud (AWS / Azure)
• Technologies / Tools: Ansible, Terraform, AWS, Azure, VPN, pfSense, Jenkins, Bitbucket, Kubernetes, GitLab Runner, ISMS, Golang, Prometheus, Grafana, S3, Lambda, RDS, ECS, Cognito, OIDC, Harbor, MinIO, Postgres, Redis, Keycloak, Ceph, Proxmox, CloudFormation, PostgreSQL, Flux CD, Hetzner, IONOS, Sonatype Nexus Repository, Entra ID, Dex IdP, Pulumi

• Remodeling of the system architecture for an Azure-based platform aimed at rapid development of new functionalities
• Modeling of a staging concept for the fulfillment of diverse customer and QA needs
• Creation of requirements for, and oversight of, a proof-of-concept supplier project for a Flutter app with highly advanced BLE functionalities
• Comparison of multiple observability platforms for feasibility and requirements fit within the project environment
• Creation of a mobile app architecture based on domain-driven architecture
• Position of technical advisor and accountable solution architect for two development teams
• Execution of architecture reviews and alignment of changes with architectural expectations
• Skills & Technologies: Microsoft Azure , App Services, NodeJS Mono-repository, microservice architecture, domain driven design, self contained systems, requirements engineering, CI/CD, DevOps, API design, solution architecture

• Held direct line management responsibility for a team of 4 Platform Engineers — owning hiring, performance reviews, and career development — while establishing a shared engineering standards framework and coaching culture that accelerated delivery across client engagements.
• Led a team of engineers to architect a cloud-native voice AI system for a major inspection client, enabling 2,500 field inspectors to document work fully hands-free via real-time transcription and AI agents — eliminating manual data entry across 440,000 inspections per month and reducing per-user cost from $9 to $1. Stack: AWS (DynamoDB, S3, Transcribe, CloudFront, API Gateway, Bedrock), ElevenLabs, Claude.
• Led a team of engineers to automate multi-region Kubernetes cluster management for a global SaaS leader, reducing provisioning time from 3 weeks to under a day and eliminating 90% of configuration errors. Stack: EKS, Terragrunt, Python, Bash, ArgoCD.
• Accelerator - Cloud-Agnostic AI Platform: Architected and delivered a cloud-agnostic, Kubernetes-native platform as an accelerator, enabling multi-tenant, enterprise-scale management of self-hosted LLMs with concurrent deployment of multiple base models and dynamic LoRA adapter serving. Designed production infrastructure using open-source tooling (ArgoCD, Karpenter, vLLM, SGLang) with automated model lifecycle management, API security (Keycloak + LiteLLM), and cost-optimized GPU provisioning.

OpsWorker turns Kubernetes alerts into root-cause analyses, on top of the monitoring a team already runs. I lead the technical side: the agent architecture, the AWS infrastructure it runs on (fully inside EU regions), and the engineering decisions behind it, read-only in the cluster by default, human in the loop for judgment. The stack underneath: Amazon Bedrock and Bedrock AgentCore, agents built with the Strands Agents SDK, the Claude and OpenAI APIs, and the Kubernetes API.

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.

• Architecture and implementation of a fully digitalized closing flow for managing securities contracts within the DVAG infrastructure. The platform aims for maximum user-friendliness, modular extensibility and compliant handling of sensitive data.

• Implementation of a reactive UI structure with a focus on user guidance & accessibility.

• Dynamic control of form and closing processes including validation logic.

• Reactive state management via SignalStore (signals + selective effects).

• UX optimization through adaptive components and Playwright-based UI tests.

• Backend modularization to connect existing sales and contract logic.

• API stability and DTO design according to Clean Architecture principles.

• Collaboration with domain teams to define technical contracts and service boundaries.

• Management with GitHub.

• Unit tests with Jest, E2E tests with Playwright.

• Code reviews, CI-integrated test execution, iterative refactorings.

• Ensuring high coverage and UI stability in the closing flow.

• Technologies: Angular 18, RxJS, SignalStore, HTML5, SCSS, Spring Boot, Kotlin, REST, OAuth2, Jest, Playwright, Clean Architecture.

• Developing automated build and deployment processes for the exclusive front office systems
• Integrating the front office systems into the IT infrastructure
• Developing innovative, user-friendly sales software for financial advisors
• Ensuring quality and flexibility through automation and working with CI/CD
• Working according to DevOps principles
• Operating the software together as a team in the AWS cloud and Azure cloud
• Deploying software artifacts to testing and production environments
• Maintaining the test environments
• Performing error analysis and providing information for further root cause analysis
• Maintaining and supporting the build pipeline
• Supporting load testing
• Coordinating the batch execution schedule with batch automation
• Creating concepts to further develop the software packaging process
• Building and delivering components to partners
• Developing GitLab and Jenkins pipelines for building, deploying and integrating components
• Automating processes with Spring Boot applications with a GUI (Thymeleaf, Angular 19)
• Developing RESTful Spring Boot applications with Kotlin and Angular 19, JDBC and REST accesses, data exchange via SFTP, XML (JAXB)
• Designing components using Domain-Driven Design (DDD)
• Replacing cmd and bash scripts with Spring Boot applications with a GUI
• Replacing Java 8 applications with JSP by Spring Boot 3 applications (Thymeleaf, Angular)
• Implementing frontend and backend authentication via Keycloak
• Writing JUnit tests with Mockito
• Increasing code coverage for SonarQube analysis

• AI-supported source code analysis
• AI image generation for a shirt shop
• AI-supported analysis of connected YouTube channels and commenting users
• AI-supported software prototyping
• Operation of a local AI environment
• 3D printing and scanning: development of a process to repair GfK parts using 3D-printed negative molds

The focus is on practical applications of new technologies, founding an open-source project for a yacht autopilot, as well as yacht refit and motorhome conversion.

• Implementation of specified DevOps solutions to automate infrastructure (Terraform, Bicep, CloudFormation, Ansible) on-premises datacenter (Ovirt, Proxmox, Ceph Cluster, MinIO) and private cloud.
• Administration, configuration and implementation of CI/CD DevOps pipelines (GitLab, GitFlow) to support development process (Artifactory, Prometheus, Istio, service mesh, Helm Chart, OpenShift (Red Hat Enterprise) / Kubernetes cluster), Red Hat Satellite.
• Administration, setup, monitoring and patching of Linux infrastructure based on Red Hat Enterprise for Dev, Test and QA.
• Use of Scrum and Kanban methods.
• Administration, configuration and implementation of security standards for deploying on Dev, Test, QA and Prod stages of the new ePA applications.
• Development of new plugins and add-ons needed on current infrastructure.
• Database support.
• Data analytics support (Python, Spark, Pandas, Power BI, Splunk Enterprise).
• Implementation of best practices for DevSecOps and BizDevOps using GitOps (ArgoCD), Streamlit framework, Semaphore Ansible UI.
• Configuration and testing of iperf, uperf, sysbench using benchmark-operator for external source data and IoT/MDM devices, creating reports via ELK / OpenSearch.
• Building a new Databricks platform to collect and analyze big data from different sources and IoT devices into Hadoop framework (Python, Pandas, PySpark, Power BI, Apache Airflow).
• Building backend data aggregation and processing to automate configuration deployment between different OpenShift clusters and big data framework (Python, Pandas, PySpark, Apache Spark, PostgreSQL, Django 2, Ansible Automation, Jira JSM).
• Building a new ML pipeline platform using Kubeflow, TensorFlow, KServe.
• Data extraction, transformation and loading from different data sources including structured and unstructured data to analytic DWH / big data cluster using Python, Pandas, Polars, Power BI, Django backend and PostgreSQL.
• Setup of new DevOps Test and QA HashiCorp Vault cluster for PKI and IAM.
• Configuration and testing of automated patching based on CVSS score, SIEM-integrated CVEs.
• Use of Nexpose and InsightVM to scan vulnerability events in network, host, container and application.
• Design and implementation of secure and scalable AWS architectures including VPC, EC2, S3, RDS and Route53 and similar setups on Azure and GCP.
• Automated system provisioning and deployment using CloudFormation templates.
• Configuration of IAM roles, policies and permissions to ensure secure access control.
• Patch management, backup automation and disaster recovery setup on AWS infrastructure.
• Monitoring and optimization of system performance using AWS CloudWatch and AWS Trusted Advisor.
• Support of VMware services (vSphere, Aria, Horizon) and the virtual desktop environment.
• Development and maintenance of CI/CD pipelines using Jenkins, GitLab CI/CD and AWS CodePipeline with interface to Nutanix.
• Configuration of AWS CloudWatch to monitor application performance and system events.
• Planning and execution of migration of on-premises applications to AWS cloud platforms.
• Deployment of containerized applications using Docker and Kubernetes in AWS environments.
• Deployment of internal software packages between availability zones using AWS CodeDeploy.
• Building and deploying ML models using Scikit-learn, XGBoost and Spark MLlib including hyperparameter tuning, model evaluation and production deployment.

• Refactored the mobile app by reimplementing stores, models, API client, screens and components using Typescript
• Added performant on-device storage for stores as preparation for offline mode
• Integrated RNUILib to achieve a minimal and modern UI design quickly
• Implemented native packages to provide additional features such as displaying of caller IDs
• Planned feature development and UX improvements following initial refactoring and redesign

• Design, extension, and implementation of interfaces (REST, GraphQL, Kafka)
• Architecture and implementation of cloud-native microservices on Azure Kubernetes Service
• Domain-Driven Design, Event-Driven Architecture with Kafka
• Development of an extensive query engine for REST endpoints based on business objects
• Design and implementation of master data classification using machine learning algorithms (Weka library, Spotify Voyager)
• Analysis and evaluation of complex load test scenarios and derivation of optimizations
• Increase in system resilience (Kafka error handling, circuit breaker, sidecar service mesh in Go)
• Integration with CIAM systems (asynchronous real-time synchronization and definition of data ownership, authorization, authentication)
• Connection to Azure ServiceBus (AMQP protocol)
• Design and implementation of complex authorization concepts (including delegated administration)
• Documentation of the results (Confluence, architecture descriptions, architecture decisions)

• Extended the document management system with a standard CMIS (Content Management Interoperability Services) interface
• Implemented CMIS core services like navigation, access rights, search, CRUD operations, and versioning in Java
• Implemented based on RESTful / OpenAPI services
• Delivered as a fat-jar and native container image
• Deployed on-premises and serverlessly as an Azure Container Application using Terraform
• Improved team autonomy through infrastructure engineering and short feedback loops
• Established observability with OpenTelemetry, Azure Monitor, and Azure Logic Apps
• Introduced Terraform and trunk-based development processes
• Ensured quality with BDD tests in C# using SpecFlow and Testcontainers
• Created Azure DevOps pipeline integration tests
• Introduced cloud deployment processes
• Trained staff in cloud and Terraform