Tailwind CSS Experts in Munich

Project: Tax Exemption Order Application

The client has an existing application for creating and maintaining tax exemption orders for end customers; design and implementation of a comparable application for internal employees.

• Design and implementation of microservices and the UI for the business area "tax exemption orders" using Domain Driven Design as well as Spring Boot and Angular.
• Implementation of reactive, non-reactive, and asynchronous APIs (Spring REST, WebFlux, GraphQL).
• Development of the Angular application, including state management using Signals, RxJS Observables, and subscriptions.
• Securing the API and the application using OAuth2, JWT, and OpenID Connect.
• Configuration and setup of CI/CD pipelines with Jenkins.
• Collaboration with cross-functional teams and conducting code reviews.

Environment: Java, Spring Boot, Angular 18 & 19 (standalone, signals), RxJs, Bootstrap CSS, Vitesting, OpenShift, Istio, microservices, Kafka, Dynatrace, Jenkins, GitLab, Graylog, Sonar, Oauth2, OracleDB

• Design and implementation of a Laravel backend API for provider-based geo search, feature details, boundary geometries and neighborhood detection.
• The API serves as a server-side proxy, cache and enrichment layer, protecting credentials for external geo services and persisting features, localizations, geometries, hierarchies and neighborhood relationships in MariaDB.
• Key areas included normalization of autocomplete and feature data, caching strategies for expensive boundary/polygon requests, spatial processing of GeoJSON and MultiPolygon geometries, as well as neighborhood detection using hierarchies, bounding box filters and topology checks.
• Additionally, separate production and diagnostic endpoints were created, along with status and error catalogs, discovery logging, a Docker development stack, API documentation, and unit and feature tests.
• Technologies: PHP 8.3, Laravel, REST API, geo data API, GeoJSON, MariaDB Spatial, Eloquent, Laravel Queues, PHPUnit, Mockery, Docker, Docker Compose, API design, geocoding, boundary data, spatial queries.

• Designed and developed the "Credit Risk Engine" using Camunda, Node.js and Typescript
• Greenfield project for credit card credit assessment for existing and new customers, including EBA KPIs, SCHUFA and CRIF scorings
• Built and modeled workflows (BPMN) and decision logic (DMN) with Camunda Modeler in close collaboration with stakeholders
• Implemented service tasks, user tasks and jobs with Nest.js, Node.js and Typescript, including exception handling
• Backend-for-Frontend (BFF), frontend with React, Tailwind and Ant Design UI library
• CI/CD with GitLab, Kubernetes/Rancher

• Role: Software Engineer & Applied Mathematician (Mathematical optimization for scheduling; duration: 1 months; team setting: Team of 2, remote; technologies: JuMP, Julia, Pluto, Svelte, JavaScript, TypeScript, JetBrains Space, Terraform, Nomad)

• Role: Software & Cloud & Web Engineer (Building scalable data science compute cluster from scratch; duration: 11 months; team setting: Team of 1, on-site; technologies: Terraform, Kubernetes, k8s ingress, k8s services, k8s RBAC, k8s networking, k3s, etcd, S3, DNS, certificates, Julia, Pluto, JavaScript, Tailwind, Astro, npm, Parcel, Preact, MUI, JWT, AWS SQS, AWS RDS, Python, GitLab, GitHub)

• Role: AI & Web Engineer (Custom ChatGPT service; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Poetry, LangChain, Tailwind, ChatGPT API, Flask, FastAPI)

• Role: Architect & Data Engineer (Central datalake setup and ingestion; duration: 9 months; team setting: Team of 5, remote; technologies: Infrastructure-as-code, AWS CDK, Python, Boto3, PySpark, AWS Glue, IAM, S3, ECS, Fargate, Lambda, Apache Hudi, DeltaLake, Databricks, GitHub, Jira, Miro)

• Role: Software Engineer (PoC Julia migration of scikit-decide; duration: 1 months; team setting: Team of 2, remote; technologies: Python, Julia, GitHub)

• Developed dynamic web components for displaying KPIs, intelligent map applications, and operational process analysis tools
• Angular 18+
• Leaflet, MapLibre
• NestJS, JavaScript, HTML, CSS
• PostgreSQL, GraphQL, RabbitMQ
• Gitea, Jenkins, Docker

• Computer vision engineer responsible for development of industrial vision solutions, beginning as a working student and transitioning to a full-time role in May 2025.
• Designed and implemented vehicle detection and counting models; integrated the pipeline into a cloud-deployed system (Azure) that delivers live analytics dashboards.
• Building an offline print quality assurance system that scans corrugated-board prints on production lines to detect and classify defects such as splashes, impurities and colour deviations, deploying the solution on Jetson edge devices.
• Collaborated with cross-functional teams while focusing on computer vision components, containerization, and deployment.

• Designed and developed end-to-end web and mobile products as a full-stack engineer, working across Python/FastAPI backends, databases, and React / React Native frontends.
• Built LLM- and agentic-AI systems using LangChain, LangGraph, CrewAI, Langfuse, and vector databases, focusing on reliability, observability, and clean abstractions.
• Developed a text-to-SQL assistant for the marketing team that lets non-technical users query a large retail-style dataset in natural language, returning clear analytics and campaign insights.
• Helped reduce ad-hoc SQL/reporting requests to engineering by 60% and cut time-to-insight for common marketing queries from hours to minutes.
• Created a full-stack mobile app where Apple Health data is processed and fed into an LLM to generate personalised, VO2-max–based health coaching and insights, owning architecture from frontend to backend and auth.

As part of an in-house development project, a pipeline for automated lead generation was created as the second stage of a preceding system for project monitoring. Based on a list of freelance project URLs (freelancermap), qualified lead records are generated, including company, contact person, official and personal email address, and the appropriate form of address (informal/formal). The technologies used were Python (openpyxl, requests) as well as an LLM agent workflow in VS Code (GitHub Copilot Chat) with a custom slash command and extensive rule set; search APIs (Serper.dev) are connected for research. My tasks included the full concept and development. The core is a rule set of around 480 lines that guides the LLM agent deterministically through extraction, website and email lookup, duplicate matching (against existing provider lists), and the creation of a structured JSON output. Deterministic steps (Excel matching, web/email search, pattern derivation) were moved into Python helper scripts. Other requirements included validating the results through versioned blind runs against a reference, iterative refinement of the rule set, and a swappable search provider layer for cost and stability reasons.