Large Language Model Experts in Hamburg

As a Council Member at GLG (Gerson Lehrman Group), the world’s leading expert network, I provide organizations, investment firms, and consulting companies with expert discussions on demand – wherever specialized knowledge in information security, IT governance, and regulatory compliance is needed.

My assessments are based on many years of practical experience in highly regulated industries: from building and implementing information security management systems (ISMS according to ISO 27001), IT risk and vulnerability management, and business continuity (ISO 22301) to the practical implementation of European regulations such as DORA, NIS2, BAIT, and the Cyber Resilience Act (CRA).

The cooperation is project- and discussion-based. I provide decision-makers with a practical perspective gained from real-world experience on cyber risks, security governance, and operational resilience – exactly when it is needed.

• Designed and moderated a NIS2 preparation workshop for RAS Reinhardt Maschinenbau GmbH and its IT service provider Catuno GmbH. Together with executive management and IT leadership, the current status was assessed, an initial GAP analysis was conducted and areas for action were prioritized based on ISO 27001.
• Developed an ISO-27001-based regulatory framework (ISMS) for NIS2 compliance, including a structured current/target GAP analysis, targeted improvement of the security maturity level and preparation of the organization for NIS2 audit readiness.

• Owning RAG, LLM-System, ML-ops-Pipelines for various startups in Insurance, Banking, Energy (KRITIS)

• Orchestrate cross-functional delivery across organisational units in the Connectivity domain, aligning teams around integrated end-to-end, customer-testable value rather than isolated component delivery.
• Drive a shift from local component optimisation towards shared outcomes and a common delivery goal, increasing focus and enabling significantly faster integrated delivery.
• Coordinate across 15 cross-functional organisations in a highly complex OEM environment; bring Product, Engineering, Programme Management and specialist functions together to resolve dependencies and improve decision-making.
• Coach Product Managers, Product Owners and stakeholders on product responsibility, prioritisation, outcome orientation and aligned backlogs.
• Use Claude through an AWS Bedrock integration to analyse Jira and Confluence content, identify patterns, dependencies and quality gaps, and support structured product and delivery decisions.
• Establish AI-native requirements excellence with LLM-supported quality gates for epics, features, stories, acceptance criteria, roadmaps and task breakdowns; scale adoption through templates and prompt playbooks.

• Assumed responsibility for backend architecture and technical strategy, planning and leading the platform's evolution in close collaboration with the CTO
• Simultaneously drove the development of new features for the housing and tenant management platform, balancing high-level architectural design with hands-on implementation
• Utilized AI-assisted workflows (with tools such as Claude Code, Codex, Cursor) and worked on AI-based features (with tools such as N8N, Mastra, ElevenLabs)

Technologies: Node.js, TypeScript, React.js, Next.js, PostgreSQL, Google Cloud, Docker, Kubernetes

Technologies: n8n, Notion, OpenAI API, Claude, MS AI Foundry, MS CoPilot Studio, MS CoPilot, LLM, Node.js, Vercel, LangGraph, PostgreSQL, pgEdge, pgvector, Docker, LangChain, Ollama, Open WebUI

• Continuous evaluation and prioritization of internal automation needs
• ~20 AI agents in active use: research, content pipelines, document processing
• 5 n8n workflows for automated data and process control
• Architecture built on the same principles as in customer projects: state management, event-driven orchestration, API integration
• Ongoing operation and further development

• Implementing cross-industry applications with LLMs
• Developing cloud infrastructure for clients
• Implemented end-to-end data pipeline to deploy models in real time
• Managed overall IT system administration and desktop support

Self-directed exploration of agentic AI development methods, taken from idea to a working, publicly usable application

• Built an interactive planning tool for modelling retirement withdrawals and tax strategy using an agentic AI (vibe coding) development approach – demonstrating self-directed investigation of new AI-assisted development methods
• Delivered live, tax-aware spending projections and adjustable user inputs; shipped as a free, install-free browser application built in Python, with attention to usability for non-technical users

• Calculation of attribute importance based on driver analyses
• Interpretation, reporting, and consulting

• Sole technology owner, leading architecture, development, operations, and infrastructure. Leveraging AI to accelerate work in areas like front-end and design.
• Built full-stack solutions (backend, React front-end) with CI/CD pipelines and observability standards, setting the foundation for an engineering organization.
• Delivered AI-driven features using LLMs, automating supplier–buyer matching, lead generation, email campaigns, and reducing manual effort.
• Reduced cloud costs by 90% by migrating the system to an AWS serverless architecture

• Industry: SaaS (Customer Success Management) – B2B

Comprehensive GEO implementation (Generative Engine Optimization) for a B2B CSM SaaS startup with a focus on AI Search Visibility and AI Citations in ChatGPT, Perplexity and Google AI Overviews – including a GEO workshop and a prioritized implementation roadmap.

• GEO Workshop & Roadmap: Conceptualized and delivered a GEO workshop (how LLMs work, AI Search Architecture, citation strategies); translated it into a prioritized implementation roadmap with impact/effort estimates
• Technical GEO Foundation: Robots.txt & llms.txt, Core Web Vitals & page speed, XML sitemaps for AI crawlers
• Schema & Structured Data: Gap analysis, implementation of Product/Service, FAQ, Article, Author and Organization schema, validation of coverage
• Content Architecture & GEO: Flat content architecture, topic clusters (pillar-and-spoke), 200–300 word chunks and answer-first content structure, E-E-A-T rollout through author pages
• Query Fan-Out & Prompt Anticipation: User prompt mapping, query fan-out, content gap analysis based on prompt coverage
• Citation & Backlink Strategy: AI citation analysis (news, Reddit, Wikipedia, listicles) and development of outreach and backlink strategies

Tools & technologies: Otterly.AI, PeecAI, Qforia (iPullRank), Schema Markup Validator, OpenAI Tokenizer, Prompt Coverage Monitor, ChatGPT, Perplexity AI, Semrush, Ahrefs, Framer CMS

Freelance work for a large German family office

Built and further developed a modular B2B SaaS platform for professional wealth management and family offices, alongside freelance delivery of production-ready AI, data management, and automation solutions for the wealth management sector.

• Developed an AI governance framework for regulated finance and asset management workflows, aligned with DORA, BaFin-related governance expectations, and data protection requirements, including role definitions, access levels, and decision rules.
• Designed an agentic system with a locally operated open-source language model, including Qwen2.5 via Ollama, for secure querying of an asset database through text-to-SQL-to-text workflows.
• Built AI-supported analysis and reporting capabilities that generate structured answers, tables, and charts from asset data, with domain validation through resolver logic and RAG elements.
• Developed production-grade data import workflows for financial service provider data from CSV, PDF, and API sources, including validation, plausibility checks, and reconciliation with existing asset data.
• Solved the asset matching problem without a cross-system primary key through multi-stage validation rules and human-in-the-loop approvals.

Results:

• Secured EUR 250,000 in SaaS revenue in 2024, exceeding the forecast by 20%.
• Acquired family office clients with EUR 1.6bn in assets under management.
• Reduced manual effort for the largest client by approx. 3 days per month through automated data import and reconciliation processes.
• Reduced operational error risk through structured data validation, multi-stage asset matching, and human-in-the-loop approvals.

• Development and implementation of custom IT solutions for key customers.
• More than 15 years of experience in IT and project management, disciplinary leadership of up to 80 employees.

• Reviewing functional and technical requirements from a testing perspective
• Creating test cases and automated tests to validate requirements
• Performing manual and automated functional, end-to-end, and regression tests
• Documenting test results and tracking defects
• Using models like GPT-4, BERT, and Hugging Face Transformers for automated test case generation, analysis of test results, and improving test coverage, including bias checks and security reviews
• Techs: MS Office, Jira, Zephyr, Confluence, Tosca, stakeholder communication, Agile, Kanban, Scrum, OpenAI API, Hugging Face, PyTorch, LangChain.