Event-Driven Architecture Experts in Berlin

• Acted as technical consultant to optimize multi-layer ensemble models combining ResNet, CNN-BiGRU-Attention, and XGBoost.
• Guided implementation of a Logistic Regression meta-learner to solve class imbalance problems, achieving 92.86% accuracy and 0.9644 AUC on PTB-XL and Chapman-Shaoxing datasets.

• Building independent projects in the AI/developer tools space.
• Experimenting with product ideas, rapid prototyping, and go-to-market validation.
• Designing AI-native operating model—leveraging agentic pipelines, living context schemas, and rigorous eval harnesses to multiply individual contributor leverage and eliminate implementation bottlenecks.

Through Sourcegarden GmbH, ongoing engagement. Transitioning software development to agentic development in phases, from setup and pilots through transformation and handover.

Company in the industrial sector

Projects completed during retraining

• Rebuilt the company website from WordPress using a modern stack with Astro and TypeScript, deployed on Vercel (live at sybarium.vercel.app); replaced the legacy CMS with a faster, maintainable system.
• Reduced page load time by ~80% (from 5 s to under 1 s) through optimization, caching, and asset optimization.
• Developed n8n automation workflows that integrate several REST APIs and internal systems, saving more than 3 hours of manual work per week.

• 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

• Building a full-stack e-commerce product using AI-assisted development, deliberately returning to hands-on engineering to validate how AI changes software development workflows and team dynamics.
• Exploring VP Technology, Head of Engineering, and Director of Engineering opportunities where hands-on AI experience meets organisational scaling expertise.
• Open to advisory conversations on AI-augmented engineering teams, technology strategy, platform architecture, and organizational design.
• No registered business. No commercial activity.

• Bootstrapping a CloudOps team and building a multi-cloud provider backend for a low-code Internal Developer Platform (IDP) with env zero

• Introducing user story mapping, ADRs, milestones, and backlog management

• Designing and developing core APIs, setting up CI/CD pipelines, OpenTofu/Terraform scripts

• Representing and communicating the team with third-party stakeholders (e.g. env zero)

• (Cross-)team coaching on DevOps, software design, Terraform, Golang, and agile practices

Java 21 · Spring Boot 3 · Keycloak · PostgreSQL · Docker · Nginx · GitHub Actions · DigitalOcean · React 18 · TypeScript · Plasmo

• Architected and shipped a production-ready Job Application Tracker end-to-end: REST API with 5-stage workflow, pagination, sorting, and dynamic filtering — full ownership from design to live cloud deployment on DigitalOcean.
• Implemented production-grade identity management: OAuth 2.0 / OpenID Connect / JWT / RBAC via Keycloak, applying Hexagonal Architecture and DDD principles.
• Built automated CI/CD pipeline (GitHub Actions); containerised with Docker; Nginx reverse proxy with path-based routing and SSL termination.
• Developed a Chrome Extension (Plasmo framework, Manifest V3) that auto-fills job applications directly from LinkedIn into the tracker — demonstrates full product thinking across backend API and browser client.

• Leading engineering organization of 45 engineers across 8 teams while serving dual role as Head of Backend
• Addressed critical organizational challenges including siloed departments, lack of engineering processes, and absence of technical strategy
• Executed comprehensive engineering leadership in people management, organizational design, and strategic planning
• Drove platform modernization including migration to a new Python backend, implementation of React micro-frontends, and transition to event-driven architecture
• Established engineering excellence framework through Architecture Decision Records, RFC processes, and comprehensive technology roadmapping
• Transformed engineering into integrated business partner by building collaboration channels with Product Management and Customer Operations teams
• Reduced escaped bugs by 50% and increased test coverage in legacy systems
• Achieved 100% Q2 roadmap delivery through realistic planning and improved estimation accuracy
• Introduced AI engineering strategy, establishing policies, providing tools, and training team on prompt engineering and agentic workflows
• Saved €10k monthly through infrastructure optimization including AWS IoT to RabbitMQ migration and decommissioning legacy systems
• Improved team engagement from 60% to 100% survey participation and enhanced eNPS scores among team leaders
• Built high-performance team through strategic hiring of Python, Go, and frontend engineers and improved onboarding
• Implementing transition to self-organized cross-functional teams

• Project 1: Multi-Tenant SaaS Platform: Data Integration & Pricing Management
• Objective: New development of ELT pipeline (replacement for Java 6 legacy), integration of heterogeneous source systems (CSV, Excel, Email, external DBs), event-sourcing for complete auditability, multi-tenant architecture for tenant-capable data processing
• Challenge: Processing millions of records daily, audit compliance, data isolation between different tenants
• Solution: Stakeholder workshops for requirements analysis, event-driven architecture with Axon Framework and Apache Kafka, AWS services (EC2, S3, Lambda, SQS, API Gateway) for cloud integration, PostgreSQL with tenant-specific schemas for multi-tenant data isolation, REST API design with Spring Boot for external system integrations, comprehensive testing strategy (JUnit, Spring Test, Postman, PACT, ArchUnit)
• Results: ELT performance improved from 30+ min to 1-5 min; 2-3 hours daily saved through workflow automation; 10-20 hours/week saved through event-sourcing auditability; 100% audit compliance; secure multi-tenant data isolation for 10+ tenants
• Project 2: Multi-tenant CRM System Modernization
• Objective: Migration of CRM system (20+ years PHP/MySQL) to Java microservices, Domain-Driven Design implementation, establishment of Test-Driven Development, multi-tenant-capable SaaS architecture for multiple customer tenants
• Challenge: Remodeling complex business logic, no existing test culture, scalable tenant management with data isolation
• Solution: Comprehensive testing strategy (JUnit, Spring Test, Postman, PACT, ArchUnit), multi-tenant architecture with tenant-specific databases, REST API design with Spring Boot for cross-tenant integration, Kubernetes and Docker for container orchestration
• Results: 2× performance improvement; deployment time reduced from 40+ min to 5-7 min; migration without production outages; scalable multi-tenant solution for 15+ customer tenants
• Technologies: Java, Spring Boot 3.x, Angular, Apache Kafka, AWS (EC2, S3, Lambda, SQS, API Gateway), PostgreSQL, Axon Framework, Kubernetes, Docker, GitLab CI, REST API

• 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

• Developed high-performance APIs for SDK backend on JavaEE Web, iOS, and Android, improving application performance and scalability by 30%.
• Led system design, tech stack planning, and development, ensuring 98% uptime with strong code quality and automated tests.
• Implemented CI/CD pipelines with Jenkins and GitHub Actions, reducing release cycle time by 40%.
• Deployed cloud-native applications on AWS EC2 instances, ensuring 99% uptime and optimized performance.
• Delivered clean code with full unit, component, and integration test coverage, reducing defects by 25%.
• Collaborated across engineering, QA, and product teams to deliver secure, reliable solutions.
• Mentored team members, increased development efficiency by 20%, automated routine tasks, and contributed to hiring, growing team capacity by 15%.

• Heycar is a leading automotive platform redefining the used car market through intelligent data pipelines, multi-tenant services, and dealer-focused tooling. I led initiatives across backend architecture, data ingestion, and identity management to enhance scalability, reliability, and developer productivity.
• Ingestion Platform: Designed a unified ingestion platform with YAML-based configuration, enabling new dealer data pipelines to be onboarded without code changes, cutting setup time from ~2 months to 2-3 days and improving scalability by 40%.
• Keycloak Leadership: Acted as the company's Keycloak expert, scaling it for multi-tenant identity management and extending functionality with custom plugins and delegated admin APIs.
• Back-Office Tooling: Developed a back-office application integrated with Salesforce, enabling dealers to manage inventory, convert leads, and handle support requests in real time.
• Multi-Tenant Migration: Collaborated across backend teams to migrate Heycar's core services into a unified multi-tenant cluster, ensuring high availability.
• Frontend CI Optimization: Optimized monorepo delivery by implementing CircleCI dynamic config with NX, deploying only affected UI projects and drastically cutting build times.
• Observability & Mentorship: Enhanced monitoring and release reliability while mentoring backend engineers and improving code review standards.

• Developed and maintained Kotlin-based microservices with Kafka event streaming, applying Hexagonal Architecture and Domain-Driven Design in production environments.
• Contributed to the Bring-Your-Salary feature, enabling seamless onboarding of new salary accounts and improving customer experience.
• Built and integrated services for the FPAD VOP platform, supporting secure and scalable partner integrations.
• Investigated and resolved production incidents through root cause analysis (RCA), implementing fixes that improved service stability and reliability.