GitLab CI/CD Experts in Berlin

• Mentor team of 6 ML platform engineers through weekly 1:1s, technical design reviews, and best practices, improving team velocity by 35% through structured sprint planning and skill development programs
• Define 2025–2026 ML platform roadmap in collaboration with Data Science, Cloud Engineering, and Product teams, prioritizing automated model governance, cost attribution systems, and multi-environment deployment strategies
• Partner with Data Science, SRE, and Product stakeholders to align ML platform capabilities with business objectives, reducing data scientist deployment friction by 60% through self-service platforms
• Architect and deliver production-grade MLOps platform supporting 50+ models in production with automated promotion pipelines, versioning, and rollback capabilities, achieving 99.5% platform uptime SLA
• Design distributed ML pipeline architecture using Metaflow and Argo Workflows (Vertex Pipelines-compatible), reducing model training time by 30% and deployment cycles from 2 weeks to 3 days through full CI/CD automation
• Build containerized ML services on Kubernetes with auto-scaling policies, resource quotas, and multi-tenancy isolation, optimizing infrastructure costs by $180K annually (25% reduction)
• Implement monitoring, alerting, and performance tracking using Prometheus, Grafana, and custom instrumentation, reducing model debugging time by 50% and establishing model performance SLOs
• Lead development of RAG-based document intelligence platform using LangChain, LangGraph, and vector databases, implementing agentic AI workflows for automated financial document processing
• Implement Infrastructure-as-Code using Terraform for reproducible environment provisioning and GitOps workflows, reducing infrastructure drift incidents by 80%
• Design role-based access control for ML platform, implement model lineage tracking, and establish audit trails for regulatory compliance aligned with enterprise IAM best practices

• Freelance product owner, scrum master and agile coach in various projects spanning from local agencies to multinational corporations in diverse industries.

• Last projects:

• Adevinta: Technical Project Manager responsible for coordination of several sub-workstreams building the world’s largest classifieds multi-tenant platform.

• Aroundhome (a ProSiebenSat.1 company): Product Manager implementing and verifying on the business side a concept for digital qualification of user requests for matching service providers.

• Peek & Cloppenburg Düsseldorf: Product Manager Mobile advising on and guiding the rebuild of Android and iOS apps.

• Visual Meta GmbH (an Axel Springer company), Berlin: Director Product co-leading the Product & Engineering department together with the Director Engineering.

• Responsibilities at Visual Meta GmbH:

• Define and deliver a 3–5 year horizon product strategy including a product vision & mission connecting to existing company strategy and strategies from adjacent departments.

• Refine an existing OKR process together with OKR master and directors of other departments to increase focus and outcome.

• Support the Director Engineering in creating a platform transformation strategy to transform a monolithic on-premise tech stack into a service-oriented, cloud-based architecture and establish a domain-based organizational setup.

• Accountability for a motivated and talented team of 5 head-level colleagues and 17 operational team members from product management, data and UX/UI design.

• Key achievements at Visual Meta GmbH:

• Defined and delivered a 3–5 year horizon product strategy including a product vision & mission.

• Increased focus within OKR process by moving from 10 company-level objectives to 2 and from several hundred team-level key results to a few dozen.

• Created a career path framework for the product team defining roles and responsibilities from junior to head level positions.

AI Platform Backend – Senior Developer

Brought in to design and build a backend for an AI platform from scratch, including multi-provider LLM orchestration and real-time infrastructure for AI influencer personas at scale.

Tasks and responsibilities

• Architected and implemented a multi-LLM orchestration layer with Semantic Kernel to integrate GPT-4 and other providers for core platform logic and AI influencer personas, reducing model-switching overhead by abstracting provider APIs behind a single interface.
• Designed and developed a backend from scratch in C# / .NET 10, including domain modeling with DDD, a versioned RESTful API layer, and cloud infrastructure setup on Azure.
• Built a real-time chat infrastructure with Server-Sent Events (SSE), message persistence, and delivery guarantees for live operation of AI influencer personas at scale.
• Developed a media management service with integration of cloud object storage for upload and retrieval of influencer-generated content.
• Created an integration and unit test suite with data seeding for reliable regression testing across all core platform flows, significantly reducing the production error rate.

Tools and technologies: C#, .NET, ASP.NET Core, Python, TypeScript, MySQL, Semantic Kernel, EF Core, Minimal APIs, LLM Orchestration, Prompt Engineering, Agentic AI, Generative AI, AI-Assisted Engineering, Claude Code, GitHub Copilot, Google Gemini, OpenAI API, Ollama, Redis, Azure, Azure Container Apps, Azure Database for MySQL, Docker, GitHub Actions, Clean Architecture, Vertical Slice Architecture, CQRS, Domain-Driven Design, REST API, xUnit, Integration Testing, Unit Testing, Jira, Confluence, Scrum

• Led migration to GCP using Terraform, GKE, and GitOps, improving deployment consistency and scalability
• Implemented Datadog observability stack via Terraform and datadog-operator
• Established automated end-to-end tests and on-call processes, improving incident response and service reliability
• Migrated from NGINX Ingress Controller to Kubernetes Gateway API (NGINX Gateway Fabric)
• Migrated stateful services (PostgreSQL and Redis) to GCP, improving scalability and operational reliability

• Developed and deployed microservices in Kotlin and Spring Boot, integrated AWS Secrets Manager to secure credentials and decreased network calls using Spring cache.
• Refactored Kafka consumer using Spring Kafka with semaphore-based backpressure to cap records and keep heap memory stable under spikes; switched to batch upserts to cut down on database invocations; added Testcontainers integration tests for Kafka and database to pave the way for future changes.
• Automated the financial reconciliation workflow in Spring Boot (Kotlin) using Spring Scheduler, transactional boundaries, JPA/Hibernate on MySQL, and Flyway migrations, saving the accounts team 16+ hours per week.
• Designed and dockerized payments end-to-end test framework in Robot (Python) with reusable keyword libraries and profiles; integrated with GitLab CI (JaCoCo XML and HTML reports) to accelerate releases and lift code coverage to 80%.
• Implemented end-to-end observability on Datadog by instrumenting services with Datadog APM, correlating metrics and logs, provisioning dashboards, and creating monitors with burn-rate alerts and anomalies to harden reliability and give stakeholders clear visibility.

Tasks: Design and operation of end-to-end cloud data platforms for enterprise clients in publishing and finance, including infrastructure automation, pipeline development, monitoring, and data quality.

Activities:

• Built multi-layer data architectures on Databricks (Apache Spark, Delta Lake), BigQuery, and GCP
• Fully automated cloud infrastructure with Terraform across 3 environments (DEV/STG/PRD)
• Developed automated data pipelines with Python, dbt, and GCP services for different data sources
• Built monitoring and alerting systems for real-time platform monitoring
• Implemented data versioning and quality checks at every layer
• Designed automated test and deployment pipelines in GitLab and Bitbucket

Achievements:

• 2× production data processing capacity, reduced spike response time from minutes to ≤15 s, server errors ≈ 0
• Replaced 3,000 lines of manual configuration with a reusable automation module for 7 customer domains, configuration errors to 0
• Delivered a complete end-to-end data platform at ~€10/month infrastructure cost
• Migrated 7 database tables with 0 downstream issues
• Removed 100% exposed credentials, eliminated external vendor dependency
• Delivered integration of 3 teams in 1 sprint

• Development of a component library based on a design system for several international brands such as Alpecin, Karex, Linola and Plantur 39
• Integration of headless CMS, PIM and commerce solutions
• UI/UX development
• Prototype development
• MVP development
• API design and development
• SaaS development (whitelabel/multi-tenant)
• Headless CMS integration
• Design systems Digital signage
• Internationalization (i18n)
• Javascript
• Component library
• Tailwind CSS
• Storybook
• HTML
• Vue 3
• Storyblok
• Github Actions
• SEO
• i18n Theming
• React

• Insurance service provider*

Challenge: Business-critical documents were processed through external OCR providers, with ongoing costs, dependency, and data privacy risks for sensitive insurance data.

Implementation:

• Architecture and production implementation of an on-premise OCR solution with full data ownership
• Methods for recognizing document structures as the basis for automated further processing
• ML-, NLP-, and LLM/VLM-based information extraction, especially from invoices and quotations

Success: Replaced external providers: full data ownership, GDPR-compliant processing, and 75% lower recurring OCR costs per year

Used technologies: Python, Docker, Microservices, FastAPI, PyTorch, Torchvision, MongoDB, MySQL

• Manage the development release and update process for a digitized nationwide trade register project "AuRegis".

• Support software in Kubernetes/OpenShift environments, configure management with Kustomize, and implement CI/CD pipelines using Jenkins/GitLab, SonarQube, ArgoCD, and Azure.

• Oversee system release of microservice architecture.

• Craft the CI/CD stack from scratch with GitLab CI, integrating integration tests, dependency checks, and security measures.

• Automate deployment onto OpenShift using Kustomize.

• Establish infrastructure components for development, code review, and code quality analysis including SonarQube.

• Integrate GitOps tools such as Kustomize and ArgoCD, leveraging both Azure and private cloud for sensitive data handling.

• Develop Python scripts in Jenkins for cryptostore configuration and system packaging of products and microservices into deployable units.

• Automate delivery to customers and deployment on test systems.

• Craft Kustomize manifests for microservices and develop accompanying automation, treating documentation as code for clarity and reproducibility.

• Serve as technical advisor for the project's first go-live and oversee further deployments as technical rollout manager.

• Opt-in RAG extension over tenant-owned data sources (SharePoint, Confluence) on existing multi-tenant enterprise AI platform
• Architecture: ADRs, solution evaluations, permission strategy, cost modeling
• End-to-end SharePoint and Confluence connectors: OAuth consent flows, token refresh, metadata sync, search integration
• Permission resolution: ACL indexing at ingestion and query-time verification (document-level security)
• Elasticsearch hybrid search (semantic + keyword) with RRF scoring
• RAG chat with context injection and source citations
• Stack: Elastic Cloud, Elasticsearch, Docker, Northflank, Next.js, React, TypeScript, Prisma, Microsoft Graph API, Atlassian REST API, OAuth 2.0

• Planning and implementing tailored Odoo ERP solutions to support and optimize specific business processes
• Configuring and customizing Odoo modules according to individual customer requirements, including process automation and data integration
• Training and supporting end users and administrators to ensure full use of Odoo features and to enhance user skills
• Providing ongoing post-implementation support, including troubleshooting, maintenance and updates to adapt to new business requirements
• Migrating data and integrating external applications into Odoo environments for a seamless, unified data landscape
• Analyzing and improving existing Odoo systems to boost efficiency and optimize the user experience

• Conducting cybersecurity readiness checks based on an in-house assessment methodology
• Analyzing the external attack surface using the Graydaxe EASM platform
• Assessing maturity levels and deriving prioritized recommendations for action