Artificial Intelligence Experts in Dortmund

Manufacturing intelligence platform with enterprise workflows, RAG, real-time AI assistant features, and multi-repository backend architecture.

• Built and extended production AI/backend services with Django, DRF, FastAPI, GraphQL, Celery, PostgreSQL, MySQL, Redis, and WebSockets across a modular multi-repository platform.
• Contributed to ARIS V2, a real-time manufacturing AI assistant using LangChain, LangGraph, MCP tool orchestration, planning/execution flows, OpenAI, AWS Bedrock, Qdrant, and Elasticsearch/OpenSearch-backed retrieval.
• Supported rollout expansion from ARIS V1 in 4 of 17 client production plants to ARIS V2 currently active in 13 of 17 plants, increasing real-world deployment coverage to more than 50% of the client footprint.
• Worked on document-grounded RAG functionality including ingestion, OCR, chunking, embeddings, indexing, retrieval, reranking, and grounded answer generation for industrial workflows.

Stack: Python, Django, DRF, FastAPI, LangChain, LangGraph, GraphQL, Celery, WebSockets, OpenAI, AWS Bedrock, Qdrant, Elasticsearch/OpenSearch, PostgreSQL, MySQL, Redis, Docker.

• Delivered MVP-focused full-stack architecture for a health-sector client: Vite/React frontend, backend services on Google Cloud Run, and Supabase for database plus IAM/authentication.
• Supported product requirements engineering and prioritized cost-aware workload placement, implementing browser-side/edge computation where feasible before moving logic to backend services.

• Architected and deployed end-to-end machine learning pipelines across classification and prediction datasets, ensuring robustness and reproducibility through MLOps best practices.
• Contributed directly to LLM model output accuracy improvement by designing and engineering specialised prompts grounded in end-to-end ML and SciML pipeline logic.
• Developed training data for large language models by formulating coding problems that models could not resolve and subsequently documenting the correct solutions.

• Product Owner for Digital Delivery Team
• Bosch-wide digitization project for software deliveries
• Technologies: SAP EMS, JFrog, Revenera
• Running PI planning sessions

• Developed and optimised structured support workflows and evaluation procedures, applying consistent quality standards across high-volume operational tasks.
• Monitored performance metrics to identify systemic issues and drive targeted improvements — a skill directly transferable to LLM performance metric analysis.
• Managed escalations and maintained high accuracy and satisfaction standards in a fully asynchronous, remote-first environment.

Conventional Paradigm Test (CPT) – AI Evaluation & LLM Research

Development of an experimental evaluation approach to examine “paradigmatic closure” in Large Language Models — that is, the question of how far LLMs can recognize the basic assumptions, values, and limits of the paradigms within which they generate answers.

Design and testing of an additional approach to classic AI benchmarks that does not primarily measure factual correctness or task performance, but instead examines a model’s ability to recognize alternative perspectives, make implicit assumptions visible, and reflect on the limits of its own answer or interpretation framework.

Focus areas: development of evaluation criteria and test questions · LLM evaluation and comparative model analysis · prompt and response analysis · qualitative classification of model answers · study of epistemic compression and value leakage · benchmark and literature research · development of structured assessment and analysis methods

As part of CPT, existing AI evaluation approaches and benchmarks were analyzed, and a minimalist test protocol was developed that classifies model answers by response patterns such as DIRECT, CLARIFY, PLURALIST, REFUSE, and META-AWARE. TruthfulQA was used as the basis for experimental application and comparison with existing reference answers.

Technologies & Methods: Large Language Models (LLMs) · Generative AI · Prompt Engineering · AI Evaluation · TruthfulQA · Benchmark Analysis · Human-in-the-Loop Evaluation · Qualitative Content Analysis · Research & Literature Review

• Planning and executing integrated 360° marketing campaigns for mid-sized B2B clients
• Stakeholder management with internal teams, industry partners, and external agencies
• KPI-based performance reporting and deriving optimization measures
• Managing SEA budgets; keyword research and competitor analysis (ahrefs, Google Search Console)
• Scheduling and deadline management across multiple parallel client projects
• Tools: Google Ads, Google Search Console, ahrefs, WordPress, Trello, Canva, ChatGPT, Claude, Gemini

• Development of an automated job-scouting workflow for the aggregation and LLM-based evaluation of job postings from RSS feeds and APIs.
• Development of a Telegram bot for voice and text messages, featuring LLM-supported processing, summarization, and structured JSON output.
• Implementation of a personal task-planning assistant using n8n, OpenRouter, and Supabase for automated daily and knowledge organization.
• Development of LLM chatbots for structured knowledge retrieval utilizing prompt constraints, guardrails, and forced output formats.

• Technical lead of a team developing agentic chatbot solutions (React, TypeScript, Python, FastAPI)
• Architecture design for multi-LLM dialog systems - focus on maintainability, UX, and autonomous execution
• Stakeholder alignment, CI/CD processes, and AI integration at enterprise level

• Led the 12-week training program to become an AI and automation specialist
• Created training materials & video courses on "AI Fundamentals", "Working with ChatGPT", "Prompt Engineering", "AI Agents with N8N", "Automations with Make.com" & AI-generated marketing content (images, videos, blog posts & social media posts)
• Conducted workshops on the above topics
• Tools: Loom, N8N, Make.com, ChatGPT, Midjourney, Gamma.app, Canva, Kling AI, Magnific AI
• Result: Participants learn the technical and business know-how to successfully build a business as AI and automation specialists

• Setting up new desktop computers
• Setting up a VPS for automation, databases and chat interface
• Connecting to Azure AI Foundry
• Developing various n8n workflows for email, social media and document management
• Implementing a QA system (backups, error handling, HITL)
• Setting up and optimizing an inbound voice agent

• Initial assessment of requirements based on a business value prioritization framework
• Identification of issues as well as requirement gathering and evaluation using UML, BPMN, and design thinking methods for iterative requirements analysis through interviews and workshops
• Use of user story mapping in Miro to visualize and align functional requirements (e.g. correct transmission of all application data and attachments to the specialist system) as well as non-functional requirements (e.g. complete and verifiable deletion of an applicant's data) with stakeholders
• Proactive stakeholder management of internal and external stakeholders from public authorities, business units, organizations, and companies
• Preparation of status reports to communicate project progress and upcoming tasks transparently
• Responsibility for a REST-based integration solution (middleware) for secure data exchange between core systems and external specialist applications; ensuring stability and performance in day-to-day operations
• Support for Product Owners in prioritizing backlog items and in product discovery
• Communication of planning to internal and external stakeholders as well as interim assumption of Product Owner tasks and responsibilities during a staff change

• Executive responsibility for the strategic and operational management of the company with full P&L accountability
• Average 42% annual revenue growth
• Reduction of burn rate by 40%
• Significant increase in operational efficiency and transparency
• Strategic realignment and restructuring of organization, cost structure and product portfolio
• Built and led an interdisciplinary team (Sales, Customer Service, Production, Finance; 8 FTE)
• Scaled the business model by implementing structured B2B sales processes
• Operational excellence in production (error reduction > 30%)
• Established a professional customer support with a ticketing system and measurable improvement in customer satisfaction
• Implemented robust finance, reporting and governance structures (Order-to-Cash, HGB financial statements)

• Managing the company with 5–10 employees
• Planning and delivering AZAV-certified training programs