Domain-Driven Design Experts in Berlin

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 development of 15+ microservices (Java 17, Spring Boot) driving customer interactions; migrated from on-prem to GCP Kubernetes, improving scalability and reducing infra cost by 20%.
• Optimized user services with CouchDB caching and API refactoring, cutting response times by 35% and enhancing customer experience.
• Implemented canary deployments, FluxCD GitOps, and CI/CD optimizations in GitLab, reducing release lead time by 25% and enabling zero-downtime rollouts.
• Set up Grafana health checks and Anodot alerts for latency, error, and throughput monitoring, reducing MTTR by 40%.
• Built secure APIs using OAuth2, DPoP, and Gatekeeper, integrated REST and GraphQL, and achieved 90%+ test coverage with unit and E2E tests.
• Mentored junior developers, promoted Agile best practices, and collaborated cross-functionally to deliver high-impact, reliable customer-facing features.

• Designed and implemented a hybrid recommendation system (content-based + collaborative filtering)
• Built end-to-end ML pipelines including data processing, feature engineering, model training, and evaluation
• Developed RAG-based LLM systems using LangChain and vector databases for semantic search and knowledge retrieval
• Established MLOps workflows with MLflow for experiment tracking, versioning, and deployment readiness
• Implemented deep learning models (computer vision & classification) using PyTorch and TensorFlow

• IT training in theory and practice for IT specialists in application development and system integration

• Context: Healthcare and laboratory teams required faster document analysis, treatment-planning support, and reliable AI workflows for MR/VR-assisted operations.
• Contribution: Built the AI healthcare platform, model/agent workflows, VR-glasses deployment platform, REST APIs, Next.js/React interfaces, and CI/CD pipelines.
• Impact: Delivered a production-ready AI product foundation that improved clinical document review, supported laboratory automation, and made VR fleet deployment manageable across environments.

Tech: TypeScript, Next.js, Node.js, React, Java, Spring Boot, Python, PyTorch, TensorFlow, Docker, PostgreSQL, OpenAPI, GitLab, GitHub Actions.

• 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

• Developed a Generative AI-based image recommendation engine for an AI video production system
• Implemented automatic image analysis with GPT-4o
• Built semantic vector search using OpenAI embeddings, MongoDB, and OpenSearch
• Tagged and indexed 4 million customer assets
• Redeveloped recommendation engine with a hybrid, balanced keyword and vector search plus filters

• Large-scale B2C legal services platform operating across Europe in air passenger rights and in Germany across labor, mobility, and rental law.
• Owned the end-to-end onboarding and lifecycle foundations of a high-traffic customer acquisition funnel across 8 European markets, supporting ~10,000 new users per month and backed by €100k/month in paid acquisition spend.
• Led the architectural migration of the core intake and decision logic from fragmented legacy flows into a scalable workflow engine, increasing reliability, improving operational efficiency, and enabling faster iteration on funnel performance and user experience.
• Partnered closely with engineering, operations, and commercial stakeholders to optimize activation, manage complex edge cases, and ensure the platform could scale sustainably across markets without compromising performance or consistency.
• Introduced foundational product analytics and performance monitoring to increase visibility into activation, drop-offs, and lifecycle behavior, enabling data-driven prioritization and experimentation.

• Frontend modernization (multiple client engagements): Angular version upgrades, architecture refactoring, performance optimization, state management restructuring, and UI library consolidation resulting in faster load times and improved end-user experience across all projects.
• Web development: High-performance landing pages and company websites for SMB clients built with Next.js, SvelteKit, PayloadCMS, and TailwindCSS optimized for speed, SEO, and conversion.
• SaaS product development: Architecting and building an AI-powered platform for photography studio operators (PoC phase) with full-stack TypeScript: Angular frontend, NestJS backend, PostgreSQL, LLM integration (Gemini/Claude) for intelligent workflow automation.
• AI integration: Developed a PoC for AI-generated podcast avatars using the Gemini API for content production workflows.
• Angular deep dive workshops: Delivered 20+ workshops (3–5 days each, 8–10 participants) in a hands-on format where participants build a demo application modeled after their real business domain.

• 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

• Developed a SolidJS frontend UI for a spectrometric water analysis system on an ARM-based embedded Linux platform
• Prototyped UI in TypeScript React/Nx with LitElements and MQTT integration
• Built production UI using SolidJS, SUID, i18next, Ajv, MQTT.js, C3.js
• Refined requirements with UX team and water analysis system engineers
• Defined and documented system architecture, MQTT message formats, frontend architecture, and development setup
• Set up frontend system from scratch, implemented domain-oriented type system, UI components, and application state
• Managed MQTT pub/sub services and schema-based message validation in frontend
• Coached two junior frontend developers
• Worked in an agile remote team using JIRA, Git, and Bitbucket

• Provide the Price Listing Service Team Price for all cars and vans in different markets
• Adjust market-specific requirements like taxes, government subsidies, campaigns
• Import, synchronize and store new prices for all new and existing cars in Redis datastore
• Support our product and handle on-call duties
• Daily operations, developing new features, bug fixing
• Pair programming, code reviews, mob programming
• Develop POCs for new ideas
• Maintain and extend the backend
• DevOps tasks
• Perform Kubernetes updates
• Adjust and further develop Kubernetes resources
• Develop and customize Helm charts
• Adjust and update ArgoCD
• Maintain, adjust and further develop CI/CD pipelines