Node.js Expert in Berlin

• 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

• LLM-based features for automated CO₂e data extraction from unstructured documents (70% reduction)

• Agentic AI pipeline for automated Scope 3 emissions calculations with 150.000+ validated data records

• Intelligent API workflows for real-time carbon footprint calculations in ERP and ESG systems

• ML algorithms for predicting emissions hotspots and optimizing product design

• Automated data validation pipelines with NLP for quality assurance of CO₂e datasets

• Led a 15-person cross-functional team in developing 10+ AI features

• Strategic product planning and AI roadmap with 35% shorter time-to-market

• Stakeholder management with DAX companies (40% higher satisfaction, 95% retention)

• On-time project delivery with 95% budget adherence through data-driven backlog management

• Agile methods (Scrum, Kanban) with continuous AI/ML integration (25% increase in team velocity)

• Product-market fit for AI features through A/B testing and analytics (60% higher adoption rate)

• Ran structured venture discovery across five fields (real estate, trades & property management, psychotherapy & coaching, social impact). Conducted 100+ interviews plus surveys and ad tests, with kill criteria defined upfront for every hypothesis
• Designed and built AI agents for my own workflows: voice-message transcription and summarization, a journaling app with UI, a voice assistant for task planning, plus research and discovery-synthesis agents (Claude Code, Cursor)
• Built an AI-assisted tool that crawls and values property listings to pre-screen investment opportunities
• Executed several real estate projects in Germany and abroad, from sourcing and valuation to acquisition, renovation and operations

• Delivered a new notifications platform implementation built from scratch to replace existing and upcoming services
• Collaborating with other teams to integrate more domains

Tech stack:

• Data: Scala 3, Apache Kafka, Python, Airflow, Astronomer
• BE-FE: TypeScript, NestJS, Java, Spring Boot, Vue
• Dev-ops: AWS, PostgreSQL, Docker, GitHub Actions, Kubernetes, Helm, ArgoCD

• Advising companies on building, migrating and optimising BI and reporting landscapes (Power BI, SQL, Python, ETL)

• 5 client engagements in real estate and finance since 05/2025: taking over and stabilising existing reporting, automating recurring standard and management reports, building cash-flow models

• Proposal and feasibility assessments for BI and reporting projects

• Using AI-assisted development (Claude Code) to accelerate automation, tooling and web/app development

• Custom ERP system

• Problem: A client's core processes ran on scattered, siloed Excel files with no central data storage – error-prone, hard to scale and impossible to analyse end-to-end.

• Approach: Captured the business processes and requirements, modelled the data and developed iteratively together with the business team.

• Implementation: Built a tailored, web-based ERP system with a central database, role-based modules and automated reporting – delivered using AI-assisted development in Claude Code.

• Timesheet app

• Starting point: Time tracking based on an overgrown, macro-heavy Excel template – maintenance-intensive, single-user and error-prone.

• Implementation: Migrated all functionality and VBA macros into a standalone web app with central data storage, multi-user support and automated reporting.

• Cash-flow modelling

• Starting point: The existing cash-flow model covered standing investments only; project developments were missing from steering.

• Implementation: Built and extended the CF model to include project-development cash flows.

• Optimisation: Reviewed and optimised existing CF models and expanded the KPI outputs for reporting and steering.

• 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.

Enterprise AI content categorization and AI-powered web research.

• Built multi-LLM evaluation framework with annotated data
• Iterated LLM error rates based on annotated datasets
• Implemented AI-powered web research pipeline Stack: LLM, evals, OpenRouter, Python, Node.js, TypeScript, React

• Joined the initial development team and helped transform an n8n prototype into a production-ready 0-to-1 product in a fast-paced environment.
• Owned delivery across CRM and Twilio integrations, customer communication workflows, and administrative interfaces.
• Collaborated on AI evaluation, microservice architecture, and other cross-functional product and engineering topics.
• Supported the CEO across VC communications, customer acquisition, product positioning, onboarding, documentation, pricing, and sales.

• Developed complex React/TypeScript frontend systems for highly customizable lens products.
• Designed internal tooling for validating and managing product configuration constraints.
• Led accessibility initiatives to align customer-facing applications with EU accessibility requirements.
• Worked extensively in large legacy codebases while incrementally improving maintainability and developer experience.
• Collaborated across multiple teams in an international e-commerce environment.

• ▶ Built real-time voice assistant (STT → LLM → TTS pipeline) benchmarking and evaluating multiple STT providers including faster-whisper and Azure Speech. achieved sub-3s latency, Groq API (Llama 3) with multi-turn memory - directly handling edge cases in dictation, names and passcode recognition.

• Senior software engineer focused on React, TypeScript and AI-assisted product workflows
• Build frontend systems for complex SaaS products, internal tools and operational workflows
• Recent work includes AI evaluation tooling, support reliability analysis and developer-focused QA systems
• Available for freelance and contract engagements, especially remote-first projects

• Designed, built, and launched an internal event planning web application used by over 100 department leads for a large event, despite having no dedicated testing phase.

• Ensured smooth, failure-free operation during first production use, leading to the tool being adopted for future events.

• Automated catering calculations and related workflows, significantly reducing email communication and manual computation effort for meal planning.

• Managed deployment and hosting on a Linux server using Coolify, including application setup and runtime operations.

• Hired and guided a communication designer on UX while independently owning all technical decisions and implementation.

• Self-employed · Berlin, Germany
• Co-founded the company and own the entire technical side: product architecture, backend, frontend, infrastructure and operations.
• Designed and built the Automated Booking System (ABS) as well as the core platform and payment logic.
• Development of AI-powered SaaS products, from architecture through backend and frontend to production operation.
• Technical consulting on product architecture, data protection and permissible automation.
• Building, running and monetising my own API products for AI agents, each available as a REST interface and as an MCP server.
• Full ownership of architecture, infrastructure, billing, legal texts and go-to-market.

• Azure Landing Zone architecture: Design and implement a hub-spoke, multi-region-capable Azure landing zone that provides the secure, scalable and highly available foundation for autonomous driving and parking data/ML platforms.
• Compliance through Azure Policy: Enforce security and compliance standards across Azure subscriptions via Azure Policy (guardrails, deny/audit/deploy-if-not-exists), consistently achieving top-tier infrastructure security scores.
• Infrastructure-as-Code: Automate provisioning and configuration of Azure resources with Terraform and Bicep, with changes delivered through reviewed CI/CD pipelines.
• Azure Databricks and Unity Catalog: Extensive experience operating Azure Databricks with Unity Catalog for centralized data governance, access control, lineage and auditing across workspaces.
• Monitoring and observability: Built and run infrastructure monitoring and logging with Azure Monitor, Prometheus, Grafana and Loki, covering platform health, alerting, troubleshooting and capacity trends.
• Platform at scale: Architected and operate cloud data/ML platforms supporting multi-PB vehicle data ingestion and simulation; orchestrate Argo Workflow-based recompute and autolabeling services scaling to 100k+ concurrent pods on AKS.
• Reproducible ML: Established reproducible training environments with dataset versioning and provenance tracking, enabling auditing and experiment reliability.
• Operational excellence: Automated GitHub organization management and CI/CD pipelines, improving developer productivity and deployment reliability; automated recurring operational processes.
• FinOps: Developed transparent resource utilization and cost-tracking for multi-project Azure environments.
• Leadership: Technical lead for infrastructure topics, collaborating with development, DevOps and security teams; technical interviewer and recruitment panel member for scaling the engineering team.