Vue.js Experts in Berlin

• Own full-stack development of an AI-native enterprise platform built on TypeScript, React, Vite, tRPC, Hono, and PostgreSQL, delivering AI-powered consulting workflows to B2B clients.
• Designed and shipped a multi-agent AI system using ReAct framework and Claude skills-style workflow patterns, including an intelligent PM assistant with rich system prompts, slash commands, tool integrations, and streaming chat UI.
• Architected an LLM evaluation framework: rubric-based LLM-as-judge, golden datasets, regression testing, and automated quality gating — ensuring consistent AI output quality at scale.
• Integrated LangFuse for end-to-end LLM tracing, conversation replays, and evaluation pipelines, enabling data-driven prompt optimisation that reduced token costs and response variance.
• Built with Drizzle ORM, pgvector, and knowledge graphs for structured data access, semantic search, and relationship-aware AI reasoning across the platform.
• Led TanStack React Query migration across the application — replacing manual state management with centralised caching and automatic refetching, reducing data-fetching boilerplate significantly.
• Practiced AI-native development throughout: Claude Code, Codex, Perplexity SDK, and LLM-assisted testing across the full development lifecycle. Deployed on Vercel + Azure ACA with Biome for linting/formatting.

• 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.

• Led the end-to-end delivery of enterprise full-stack web applications by driving requirement analysis, solution design, frontend and backend development, database design, API integration, code reviews, team coordination, Agile execution, CI/CD deployments, production support, performance optimization, security implementation, and stakeholder collaboration to deliver scalable, high-quality software solutions.

• Founded an AI-powered scheduling and business-management SaaS for SMBs, owning technology strategy, architecture, product development, UX, billing and go-to-market execution.
• Architected and shipped a multi-tenant platform with REST APIs, RBAC, CRM, billing and notifications, powering the manager dashboard, admin console, booking experience and iOS/Android applications.
• Led and mentored 7 software engineers, 1 DevOps engineer, 1 QA engineer and 1 UX/UI designer, while remaining hands-on across backend, frontend and product delivery.
• Built AI voice and chat agents using Python/FastAPI, OpenAI and Anthropic APIs, RAG, pgvector and tool calling; integrated Twilio, Google Calendar/Meet, Stripe and Firebase.
• Owned production infrastructure and automated delivery across separate environments using Docker, Nginx, GitHub Actions and Grafana; represented the company at accelerators and international startup events.

Selected stack: Python, FastAPI, Node.js, Vue 3, React/Next.js, React Native, PostgreSQL, Redis, Docker

• Savills is one of the world's leading property advisors with 700+ offices worldwide. In Berlin, I built core digital solutions for the valuation business, replacing legacy Access-based workflows with an enterprise-grade web app built on Vue.js.
• Frontend Architecture & Scalability: Designed scalable Vue + TypeScript frontend architecture for internal enterprise applications, integrating a Symfony backend and interactive maps.
• Legacy Modernization: Led the modernization of legacy jQuery-based systems into maintainable Vue-driven applications, improving performance, maintainability, and efficiency across business workflows.
• PDF Report Workflow Automation: Engineered Twig-based automated PDF generation pipelines that reduced manual report preparation time by ~80%, saving approximately 12h per analyst/month.
• Design System & Frontend: Built a scalable SASS-based design system using mixins, maps, functions, and reusable UI patterns for consistency and long-term maintainability.

• 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

• 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.

• 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.

• Full automation of the software development process: ticket analysis → AI coding agents → pull request → automated code review → deployment
• Multi-tenant architecture with 82 database models and real-time WebSocket monitoring
• Integration of 40+ AI tools with Claude & GPT
• Tech stack: React, TypeScript, Express.js, PostgreSQL, Redis, BullMQ
• Platform in productive use with paying customers

• 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

• Overhaul of the entire design and implementation of new UI/UX aspects using React
• Planning of the software architecture and structuring of the project for long-term scalability using Git for version control

• 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

• 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

• Design of an LLM-based agent system to control the ERP software
• Development of agent workflows with LangGraph and PydanticAI
• Planning interfaces between business logic and language models
• Planning agent orchestration
• Prototype development and demonstration

Tools: Python, Pydantic, React, LangChain, LangGraph, Linux