OpenAI Experts in Hamburg

• Building an AI & Data Consultancy Practice with the goal of helping European companies adopt Artificial Intelligence and modern data platforms
• End-to-end further development of a production system using modified coding agents (OpenCode). Tech stack: Kubernetes, Argo, Keycloak, Typescript, Grafana, GitOps, DevOps, Playwright
• Internal research project on the use of coding agents in the field of mathematical logic for creating formal models. Use of Cursor IDE and Codex, Codex CLI. Architecture design, quality control and refactoring, as well as writing code and tests. Repository (open source) available pre-launch
• Research on the role of mathematical logic as a formal language that connects IT and AI with business processes
• Project lead for collecting and deploying parking recommendations for rail vehicles with significant savings potential based on real-time data in a mobility and transport company
• Project lead for collecting and distributing process measurement points for real-time control in a mobility and transport company
• Deputy application owner for an app used for communication in the dispatching and provision of rail vehicles

• 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.

• 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

• Performed security assessments and penetration testing on Microsoft AI models for text, image, and video generation.
• Conducted prompt injection attacks through diverse input vectors, including crafted text, steganographic images, and manipulated visual elements (e.g., varying opacity and embedded content).

• Creation and planning of the content plan
• Editorial planning for 10 channels
• Image shoot (organization, coordination, execution)
• Selection of image, text and video content

• Led 0→1 launch of a small D2C product, including website and CRM flows.
• Used AI and no-code tools to rapidly prototype, iterate, and operate with minimal overhead.
• Owned end-to-end product decisions across UX, content, analytics, and operations.

• 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.

• Further development of the compliance products
• Role responsibility as a Senior Software Engineer
• Team size: 5 - 15 people
• Tools: TypeScript, Angular 18, Node.js, Nest.js, AWS, Kubernetes/Helm Charts/Docker, GitLab (CD/CI), Elasticsearch, MySQL, OpenAI, Java, RabbitMQ

• Planning, structuring and further developing product trees and categories to optimize user navigation in the online shop
• Price control and assortment management
• Data analysis and quality assurance
• Automation of business processes
• Building and optimizing automated processes for social media postings and content management
• Using AI technologies to analyze and adjust large datasets
• Creating precise prompts for complex data analyses in various application areas

• Specialized in event driven microservice architecture in AWS with NodeJS, Typescript and Vue/React/Next in the frontend

• Developed a SaaS product in the B2B sector

• Used AWS services: DynamoDB, Lambda, SQS, SES, EventBridge, Cognito; Serverless-Framework; Rest-API

• Implemented unit tests with Jest and Mocha

• Set up CI/CD pipeline with GitHub Actions

• Developed a SaaS product for organization management

• Worked with AWS Microservice architecture and event driven design

• Utilized CDK, NodeJS OpenAI-API, React, Vue

• Continued use of DynamoDB, Lambda, SQS, SES, EventBridge, Cognito, Typescript

• Maintained CI/CD pipeline with GitHub Actions