Generative AI Experts in Germany
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Meet FRATCH Experts in Germany, who have recently used Generative AI
William N.
Last position:
Power BI Solutions Architect/Engineer & AI Consultant at AVERDUNG GmbH
- Redesign of the company’s BI infrastructure: replacement of a fragmented landscape of manually maintained Excel solutions and CSV imports with a centralized Power BI environment using a unified data model as the company-wide single source of truth
- Consolidation of previously isolated reporting logic in a central semantic model – elimination of redundant files, manual data transfers and inconsistent metrics across departments
- Forecasting & Planning: Design and implementation of company-wide liquidity planning in Power BI – from business logic to a fully automated, data-source-driven planning model replacing the previous manual Excel process; enabling rolling forecasts and continuously up-to-date cash flow transparency for management
- Optimization of existing Power BI dashboards in terms of performance, structure and analytical value using an AI-native approach
- Analysis and improvement of the data model, including data quality analyses, data cleansing and consistent modeling using Star Schema, DAX and Power Query
- Incident & Anomaly Analysis: Identification, investigation and explanation of data anomalies, including root-cause analysis and specific recommendations for action
- AI Solution Architecture: Connecting Business Central and Power BI to LangDock via MCP (Model Context Protocol) for AI-supported data usage
- Development of a historical data layer as a basis for trend and time-series analyses
- AI-supported automation: Design and development of AI skills, agents, loops and processes for the automated analysis and interpretation of reports
- Automated reporting workflow: Setup of scheduled, automated email delivery of AI-generated analyses and recommendations to stakeholders
- Gathering and documentation of business requirements and coordination with business departments and IT as part of requirements engineering / product owner activities
- Breaking down overall requirements into clearly defined work packages and tasks
- Definition, prioritization and management of milestones throughout the entire project lifecycle
Tools: POWER BI, M365, Copilot Studio, MIRO, Microsoft Business Central, Microsoft Fabric, Claude AI, ChatGPT, LangDock, MS VS Code
Alwin G.
Last position:
IT Interim Manager & AI Strategist
- Founder of CheironX: AI-supported GRC management (ISO 27001, BSI IT-Grundschutz, TISAX, DORA)
- Strategic focus on Agentic AI and GenAI for modern IT Governance, Risk & Compliance Management
- IT interim management and strategic consulting
Roland C.
Last position:
Founder, Agents in Everyday Business at CXO AI OS
CXO AI OS is an agent system made up of six components. Instead of using AI as a chat window, it creates a system that understands a company’s context, makes decisions according to its rules, and acts on its behalf.
- For mid-sized companies: a guided sprint followed by ongoing operations for a team, department or prioritized cluster, based on an AI assessment
- For self-employed professionals: a program where participants build their own agent system
- Sequence in the company: assessment, prioritization, sprint, operations
- Implementation in Claude Cowork or ChatGPT Work, without coding
- Architecture: Chief of Staff, Goals, Advisors, Agents, Context, Catalog
Reinhold M.
Last position:
Business Requirements Engineer, Proxy Product Owner, Tester at AXA Konzern AG
Working Environment
- Insurance / Claims Management (Property, Liability, Automotive)
- REST-based ClaimAPI with Guidewire ClaimCenter
Scope
- Further development of the internal REST-based ClaimAPI with Guidewire ClaimCenter as the backend and various portals/front-end offices as clients, and with the following objectives: + increased AI-supported claims processing outside of Guidewire ClaimCenter + and support for all lines (property, liability, automotive).
- Further development of automated claims processing
Activities
- Interfacing IT & Business
- Design activities with documentation in Confluence, Jira: + Requirements engineering (functional and non-functional) + Design of REST endpoints and coordination with interface partners (esp. AI-colleagues) + Identification, design and evaluation of alternative solutions (moving away from a monolithic approach toward fine-grained endpoints, with code reuse across all lines if possible) + Creation / refinement of product backlog items in Jira, i.e. epics, user stories and tasks, incl. alignment with developers & POs during (pre-)refinement sessions + Using AXA Secure GPT when creating / refining user stories (description, acceptance criteria) and designing REST endpoints + Estimation and prioritization of user stories and tasks during Sprint Planning sessions + Coordination and support during the implementation of Product Backlog items + Driving decision making with preparation and presentation of decision-making documents
- Quality assurance: + Test management, including test case creation using Xray in Jira + Test execution using Bruno as REST client and in Guidewire ClaimCenter + Submission of test artifacts for PO approval + Analysis of production bugs
Methods Big Room Planning (aka PI-Planning in SAFe), Scrum, BPMN, EPK, UML, ERM, DDD
Tools / Tech Stack Teams, Confluence, Jira with Xray, OpenAPI/Swagger, REST, JSON, XML, MS Office, Bruno, GitHub repository (reading), Guidewire ClaimCenter, AXA Secure GPT (AXA's in-house GenAI solution based on Azure OpenAI)
Shamaila M.
Last position:
Founder/Kubernetes and Cloud Architect at Kubekanvas
- Developed browser based platform for kubernetes no-code deployment and cluster management
- Developed CLI in Typescript to deploy the resources in the cluster without leaving the browser UI.
- Implemented DevSecOps pipelines: image scanning, SBOM, policy enforcement, supply-chain security and used Kyverno. Implemented IAM integration for the command line utility tool.
- Designed role & permission models for Keycloak, oAuth/OIDC, social login flows.
- Used LLM to convert user intent into the diagram.
- Worked on integration with multiple Sovereign Cloud like stackIt, Hetzner, CIVO, UpCloud plus public clouds like AWS, GCP, Azure
- The technology stack includes Java, SpringBoot, Kubernetes, OpenAI, Kubernetes multi-tenancy using vCluster, Karpenter, RBAC for CLI, Helm, React
Michael S.
Last position:
IT & Test Consultant at Testing Experts GmbH
AI Readiness - Part 3: Creating an e-book on the use of AI in software testing
- Designed and created an e-book on the sensible and safe use of AI in software testing from the perspective of an experienced test expert.
- Used generative AI (ChatGPT, Perplexity Pro) as a sparring partner for structuring, wording suggestions and creating variations, with all content finally reviewed and approved using my own expertise.
- Developed practical insights into the opportunities and risks of AI in testing, with a special focus on collaboration between testers and AI instead of “tester vs. AI”.
- Title: “11 starke Gründe: Dream-Team statt Rivalen - Tester und KI sind gemeinsam unschlagbar”
- Subtitle: “Wie Mensch und Maschine im Softwaretest das perfekte Team bilden – und warum reines KI-Testing riskant ist.”
- Planned use of the e-book as a basis for workshops, customer meetings or internal training.
- Technology: Generative AI, ChatGPT, Perplexity Pro, Microsoft Word, Adobe Acrobat, many years of hands-on professional testing experience, common sense.
Paul W.
Last position:
Enterprise Architect at ePrimo GmbH
Led the end-to-end integration and migration architecture for decommissioning SAP IS-U market communication and transitioning to Salesforce Marketing Cloud (SFMC) with E.ON IT Services — covering regulated EDIFACT market messaging, a three-phase data migration (transfer of market message inventory after cutover), redesign of market communication processes, and full GDPR and German energy-market compliance.
- Designed the three-tier target architecture (SAP IS-U → NScale B2B gateway → SFMC) processing 50,000–100,000 EDIFACT messages daily within sub-5-minute SLAs.
- Architected the three-phase data migration: 36 months of historical data, zero-loss cutover of in-flight market messages, and near-real-time CDC synchronization.
- Delivered secure, BDEW/GDPR-compliant integration (AS2/OFTP2, RFC/IDoc, REST APIs, OAuth 2.0, Azure AD, AWS S3) achieving >99.5% uptime, <0.1% migration discrepancy, and RTO <4 hours.
- Applied BPMN to model and optimize the market communication processes.
Technologies: SAP IS-U, NScale, Salesforce Marketing Cloud, EDIFACT, OAuth 2.0, Azure AD, AWS S3, BPMN, Jira, Confluence, Draw.io
Jens L.
Last position:
Consulting Digital Development & Transformation at European Mar GmbH
Developed the product vision and outcome strategy for a new registry platform, designed a management workshop for strategic alignment, conducted BPMN process mapping across systems and roles, analyzed user story practices and further developed them on an outcome basis, and brought together stakeholders from business departments, management and the external development partner.
Skills: Product Strategy, Outcome Roadmapping, Stakeholder Workshops, BPMN/Process Analysis, Miro, Linear
Christian F.
Last position:
Project Lead & Cyber Security Consultant at Deutsche Börse Gruppe
- Established a cyber resilience framework for AI-accelerated threats in the Frontier AI Threat Endurance (FATE) program: capability assessments, maturity assessments and gap analyses covering cyber security, operational resilience, incident response, recovery and governance, followed by target concepts and improvement measures
- Supported action owners from specification through implementation: implementation roadmaps, decision papers, management presentations and governance reporting, as well as audit- and supervision-ready documentation; managed stakeholders from IT, Information Security, Risk Management, Operational Resilience, Business Continuity and the business units
Vili D.
Last position:
Technical Lead, Data Engineer at Mercedes-Benz Consulting
Optimized the data architecture (Medallion) to better decouple processing steps and improve transparency and reproducibility
Ensured the technical quality of data processing in Databricks by introducing schema enforcement, data quality checks, and a structured data architecture
Pipeline orchestration with Azure Data Factory
Improved and automated the development and deployment process by integrating Git and GitHub Actions
Technical leadership of the Data Engineering team (3 employees)
Led workshops to optimize and stabilize the data platform and development process
Collected and prioritized new requests and maintained the product backlog
Technologies: Microsoft Azure (Data Lake, Data Factory), Databricks, Apache Spark (PySpark), Python, SQL, Git, Confluence, Power BI, Power Apps, Dataverse, MS Sharepoint, Mural
Yulia V.
Last position:
Independent Advisor - Strategy, Transformation & AI at JV Advisory
Independent advisory practice for strategy, organisational transformation, M&A / investor work and AI/data-enabled change.
- Short-term diagnostic and problem-solving mandates: rapid strategic and organisational assessments for leadership teams and Boards, translated into recommendations and transformation roadmaps.
- Organisational redesign and AI governance for an international group of approximately 1,500 employees: structure, mandates, decision rights and interfaces; AI-readiness and data-maturity assessment; vendor evaluation and selection; capability building.
- Design of a centralised Strategy Execution / Results Delivery Office for an industrial client: mandate, governance, portfolio steering, KPI logic, decision forums and implementation roadmap.
- Selected part-time mandate with SPARS GmbH (as a Business Development and Investments Director): developed M&A pipelines, assessed targets for strategic fit and synergy potential, led commercial due-diligence workstreams and investor / partner engagement.
Patrick L.
Last position:
Senior GenAI Fullstack Developer at SBH (Schulbau Hamburg)
Remote freelance role focused on Agentic AI strategy, secure application patterns, and reusable agentic workflows for a government agency.
- Development and implementation of an open-source Agentic AI strategy for a government agency, with a focus on GDPR, security, and self-hosted solutions
- Development of reusable agentic workflows and business applications that enable non-technical employees to solve business problems independently
- Implementation of nine business applications with Single Sign-On (SSO) and Azure PostgreSQL integration on Hetzner Linux servers
Techstack: Python, Streamlit, Anthropic SDK (Claude), Azure, Linux, PostgreSQL, MS SQL, Angular
Volker W.
Last position:
Analyst – Platform Optimization at TradingView ProRealtime
Programming custom indicators with ProBuilder (for the ProRealTime platform)
6 months at RCP - Rabe Academy (basics - trading account - TWS Interactive Brokers) Focus: ETH price history - NVIDIA stock (NASDAQ and CBOE)
- 500 hours total (TradingView & ProRealTime), including approx. 1,500 hours of tick data analysis using ProRealTime
Systematic market analysis, development of custom indicators, pattern recognition.
Kareem S.
Last position:
Business Analyst & Consulting Manager at S&M Unternehmensberatung PartG
- I support medium-sized clients with their funding needs.
- I evaluate operational business processes and translate complex legal and regulatory requirements into business requirements, target models and actionable roadmap epics.
- I use Generative AI tools and automation in a targeted way to efficiently create requirements documentation, process analyses, evaluations, meeting preparation materials, customer analyses and decision papers.
Luca B.
Last position:
Founder & CEO at Lube AI
- Develop custom AI agents delivering 90%+ reduction in manual workload and significant efficiency gains
- Provide end-to-end AI strategy consulting: from digital assessment to implementation and change management
- Design and deliver tailored training programs and workshops on AI adoption, prompt engineering, and automation
- Support clients in implementing scalable AI solutions integrated with existing technology stacks
- Focus areas: AI strategy, automation, workflow optimization, and capability building
Discover over 15,000 top freelancers
Statistics of experts using Generative AI
Aggregated from the professional profiles of matched freelancers.
Experience
16 years
Position duration
2.3 years
Positions per freelancer
10
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Professional Services, Automotive
Certification focus areas
Information Technology, Project Management, Product Development
Bachelor's degree or higher
96%
Master's degree or higher
75%
Doctorate
16%
Certifications per freelancer
3
Most common languages
English, German, French
Speak two or more languages
98%
Based on our profile pool as of 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Germany are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Discover detailed Generative AI rate benchmarks:
Explore rate insightsAverage rates of experts in Germany using Generative AI
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Generative AI experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (89%)
- Professional Services (47%)
- Automotive (40%)
- Banking and Finance (40%)
- Manufacturing (37%)
- Education (35%)
- Retail (33%)
- Healthcare (31%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Generative AI Does
Generative AI creates new content from patterns learned during model training. It can produce text, images, audio, video and software code from natural-language prompts or structured inputs. Companies use it to support knowledge work, automate content flows and create conversational product experiences.
Core Applications
Generative AI appears in customer service, marketing, research, software delivery and internal operations. Common project goals include:
- Building assistants that answer questions from company knowledge
- Summarising documents, meetings and case records
- Creating product copy, images, audio or video variations
- Extracting information from unstructured business content
- Adding natural-language features to existing applications
Models and Tooling
The ecosystem includes foundation models such as GPT, Claude, Gemini and Llama, accessed through hosted APIs or deployed in controlled environments. Specialists work with prompt design, embeddings, vector databases, retrieval-augmented generation, tool calling and model evaluation. Frameworks such as LangChain and LlamaIndex help connect models with data and business actions.
Delivery in Practice
A production system needs more than a convincing demo. Professionals define data flows, permissions, fallbacks, monitoring and human review before connecting a model to live processes. They also manage context limits, latency, cost controls, output formats and protection against prompt injection or sensitive-data exposure.
When to Bring in Expertise
Freelance expertise helps when a team needs to validate a use case, select a model or move a prototype into reliable operation. It is valuable when internal data must be made searchable, when an existing product needs an assistant, or when governance requirements are unclear. In Germany, specialists may also support workshops with local teams and coordinate remote or on-site work across language expectations.
What Strong Specialists Know
Strong Generative AI professionals combine model knowledge with software delivery, data handling and product judgement. They test outputs against representative cases instead of relying on impressive examples, document limitations and make failure states visible. The best fit can explain trade-offs clearly, protect confidential information and leave behind maintainable prompts, evaluations and integrations.
Frequently asked questions
Key details about Generative AI, drawn from the questions we get asked most.
Companies use Generative AI to create content, search internal knowledge, summarise records and support customer or employee conversations. It can also extract structured information from documents and add natural-language interaction to existing products.
Generative AI handles open-ended language, images or other content, while conventional automation follows predefined rules and workflows. A strong solution often combines both: the model interprets or drafts, and deterministic software validates, routes or executes the result.
A capable Generative AI specialist may also work with Python, APIs, cloud services, data pipelines, vector databases and application security. Experience with prompt design, retrieval-augmented generation, evaluation and user experience is especially useful for production work.
The right Generative AI experience depends on the scope, data sensitivity and operational risk. A prototype may need model selection and prompt testing, while a customer-facing system requires integration, evaluation, monitoring, access controls and a clear human-review process.
Generative AI projects can usually be delivered remotely when data access, communication and approvals are well organised. On-site sessions can help with discovery, process mapping and stakeholder alignment, particularly when teams in Germany need workshops in German or English.
Look for a Generative AI professional who tests against realistic examples, explains uncertainty and documents model limitations. Ask how they handle confidential data, prompt injection, incorrect answers, evaluation criteria and fallback paths before reviewing a polished demonstration.
Generative AI specialists may work with hosted models such as GPT, Claude and Gemini, or open-weight models such as Llama. The choice depends on quality, data handling, integration needs, deployment control and the level of customisation the project requires.
Working with Generative AI often involves rapid experimentation followed by careful engineering. Freelancers may refine prompts, connect business data, evaluate outputs, improve guardrails and collaborate with product, legal, security and domain teams as the system moves toward production.
The average hourly rate of freelancers in Germany who have used Generative AI in their recent projects is 102 €, which corresponds to a daily rate of about 813 € based on an 8-hour working day.
Of the freelancers in Germany who have used Generative AI in their recent projects, 96% hold at least a Bachelor's degree, 75% hold at least a Master's degree, and 16% hold a doctorate.
On average, freelancers in Germany who have used Generative AI in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 2.3 years.
The most common languages among freelancers in Germany who have used Generative AI in their recent projects are English (98%), German (97%), and French (21%).
The most common industries among freelancers in Germany who have used Generative AI in their recent projects are Information Technology (89%), Professional Services (47%), and Automotive (40%).
The most common business areas among freelancers in Germany who have used Generative AI in their recent projects are Information Technology (89%), Product Development (85%), and Project Management (63%).
Main locations of FRATCH Experts, who have recently used Generative AI
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
Berlin 
Hamburg 
Munich 
Cologne 
Frankfurt 
Stuttgart 
Dusseldorf 
Dortmund 
Essen 
Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
