CrewAI Experts in Germany

• 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.

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

• Built a custom AI chatbot for an e-commerce client using GPT-4 and LangChain with RAG, reducing customer support ticket volume by 45% and improving response accuracy to 92%.
• Designed and deployed an intelligent document processing system using LlamaIndex, Pinecone, and FastAPI for a FinTech startup, enabling semantic search across 100K+ financial documents.
• Developed multi-agent AI workflows using CrewAI and LangGraph for a marketing agency, automating lead research, content generation, and outreach — saving 20+ hours/week of manual work.
• Created AI-powered automation pipelines using n8n, Make, and Zapier integrated with CRMs (GoHighLevel, HubSpot), reducing manual data entry by 80% for a real estate firm.
• Delivered prompt engineering and LLM fine-tuning consulting for multiple clients, optimizing AI model outputs for customer support, content creation, and data extraction use cases.
• Built production-ready REST APIs with Python and FastAPI to serve AI models on AWS and GCP, handling 10K+ daily requests with 99.9% uptime.

• Architected and deployed a production-scale GraphRAG system using Neo4j, embeddings, and multi-hop reasoning over 120M+ nodes, improving answer precision by 32%, reducing hallucinations by 41%, and lowering retrieval latency by 38%.
• Designed and implemented an enterprise agent ecosystem using Model Context Protocol (MCP), exposing internal APIs, databases, and services as secure callable tools for autonomous workflows and system integration.
• Designed and deployed a production LLM-based email routing agent using Microsoft Graph API, MCP, and Azure OpenAI, achieving 96% routing accuracy, reducing manual triage workload by 65%, and decreasing response times from 18 hours to under 4 hours.
• Implemented autonomous agent self-correction pipelines using iterative feedback loops (Ralph Wiggum), enabling reliable error detection, automated remediation, and production-safe execution.
• Developed a multimodal semantic search platform using multimodal LLMs and vector embeddings, enabling semantic discovery across 250k+ image and video assets and improving search recall by 48%.

• Hybrid/Remote
• Digitalisation introduction and optimisation of software
• Advice on the introduction of AI
• Data & AI strategy
• Interim / tech consultant
• Product, process & management
• Vendor management
• Compliance management platforms (ISO 27001, GDPR, EU AI Act)
• M&A due diligence & analysis

• Attempted founding of a platform for career development and personal coaching
• Top 3 placement in the Berlin-Brandenburg business plan competition
• Conducted independent market analysis and user research
• Built a comprehensive knowledge graph for roles, skills, and experiences
• Data transformation and setting up data pipelines on Azure

• Co-founded an AI venture focused on building production-grade LLM applications and agentic systems
• Designed and implemented multi-agent AI workflows for financial and trading applications
• Developed LLM-powered copilot architectures for portfolio analysis, trade management, and personalized user coaching
• Built on-device and edge-deployed inference applications, optimizing models for low latency, privacy, and resource-constrained environments
• Led system architecture decisions across model selection, orchestration, state management, and deployment

• Strategic transition into AI Engineering through intensive mentoring and project execution.

• Developed MASX AI, an agentic AI platform integrating LangGraph, AutoGen, and RAG for geopolitical forecasting and real-time ETL.

• Designed and delivered functional AI prototypes for prospective clients showcasing applied expertise in multi-agent systems, real-time data pipelines, and LLM integrations.

• Specialized in designing and implementing robust, secure cloud solutions for critical client infrastructure.
• Expertise in Microsoft Intune environment with a strong focus on system hardening and comprehensive policy management.
• Architected NIST and ISO/IEC 27000 compliant Mobile Device Management (MDM) infrastructure tailored for an international government defense aerospace project.
• Performed an architectural role for an offline Microsoft Endpoint Configuration Manager (MECM) environment, ensuring NIST compliance while handling complex manufacturing infrastructure.

• Architected and deployed LLM based AI agents, RAG pipelines, and vector search solutions for decision support across retail banking department.
• Developed and shipped robust AI pipelines with guardrails, error handling, monitoring, and fallback logic ensuring high reliability outcomes and compliance with data privacy.
• Developed and deployed ML models to identify transactional anomalies, improving fraud detection and risk assessment in high-volume datasets for credit risk modelling.
• Built, evaluated and fine-tuned ML models to generate propensity scores for customers used to drive personalized targeting campaigns for credit cards and personal finance/loan products.
• Developed an NLP pipeline using BERT embeddings and spaCy NER for SMS/email analysis and customer query logs.
• Trained machine learning models using Isolation Forest to classify user behaviour and detect anomalies.
• Extracted, cleaned, enriched and feature engineered datasets from different sources to build feature stores that powered ML model training.
• Led development of dashboards using Power BI, Grafana, and Prometheus to monitor model performances, KPI trends, and marketing metrics.
• Built multi-touch attribution models using logistic regression and time-decay weights to evaluate lead quality.
• Developed scalable ETL pipelines from CRM, T24, SAP, and ERP, supporting millions of monthly transactions.
• Integrated testing and CI/CD workflows for robust data pipeline deployment.

• Architect AI systems across build-vs-buy layers; guide clients on technology selection, evaluation, integration patterns, and governance to reduce risk and time-to-value.
• Implement Azure/Snowflake solutions (RAG pipelines, chatbots, data agents) including ingestion, retrieval, orchestration, and monitoring.
• Partner with stakeholders to translate business needs into deployable AI roadmaps and reference architectures; align with existing data platforms and security controls.

• Selected as one of only 38 members accepted globally from 581 applicants.
• Brought data science & AI expertise into open-source Web3 ecosystems.

• Teaching JavaScript, HTML, CSS, React, NodeJS, MongoDB, MariaDB, and Express
• Designing and preparing lessons
• Classroom teaching and one-on-one coaching

• Automating Software Development with Generative AI (Master Thesis): Architected a gen-AI prototype using agentic workflows, LLMs, and RAG, achieving €100,000 in annual savings by cutting development cycles by 60–80%. Collaborated with cross-functional teams to automate the software lifecycle, boosting operational efficiency by over 60%.
• Development of an AUTOSAR AI-Based Chatbot: Implemented an AI-based chatbot using NLP, vector databases, and RAG pipeline, enhancing documentation retrieval efficiency via REST APIs by 80%. Presented findings to senior management to secure strategic adoption and executive buy-in.
• Automation of Stubbing Processes with Generative AI: Designed a generative AI solution that automated build system processes, cutting manual deployment tasks by 60% and integrating seamlessly with Git workflows.
• Co-Simulation and RTE Standard Evaluation with Gen-AI: Accelerated compliance assessment for the RTE standard by 45% using generative AI tools and Python for evaluation.