CrewAI Experts in Germany

Development of an AI console for integration into different open source solutions (ERP, CRM..)

Development of the target architecture Integration of different AI platforms (ChatGPT, Anthropic, Perplexity) Workflow with cross-platform use of the AI platforms Voice input and voice output History Console-based project management Generation of custom agents (Crewai..) Integration of the agents into the AI workflow

• 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.

• 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.

• 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.

• 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%.