
Generative AI Experts in Munich
matched in minutes from over 15,000 CVsHire experts who design LLM applications, retrieval-augmented generation systems and reliable AI workflows. FRATCH connects you quickly with vetted, available freelancers whose skills match your Generative AI project precisely.
Meet FRATCH Experts in Munich, who have recently used Generative AI
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
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
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.
Hachem S.
Last position:
Machine Learning & BI Lecturer at EU Business School
- Taught ML, BI, and Big Data to Master's students.
Tech: Python, Power BI, SQL, ML, SnowflakeDB, databricks, MS Fabric, MongoDB, LLM
Michael N.
Last position:
Senior AI Engineer | Forward Deployed Engineer at Tiefbau
- Development of an AI-powered project organization tool for a civil engineering company that intelligently links project, task, tender, schedule, and document data through a knowledge graph.
- Implementation of AI features for document analysis, information extraction, context-based assistance, and voice-based data capture based on Microsoft Azure AI, reducing administrative effort, making information available faster, and supporting project teams in decision-making.
- Tech stack: Python, React, TypeScript, FastAPI, Claude Code, Codex, Graphify, PostgreSQL, Microsoft Azure AI Foundry, Azure OpenAI, Azure AI Speech, Azure AI Document Intelligence, Microsoft Graph, Microsoft Entra ID, Docker, Git, CI/CD.
Mirza K.
Last position:
Agentic Automation and a RAG system
- This project involved extraction of intelligence data to support report writing for a company that provides geopolitical, global, commercial intelligence. The data have been gathered from a number of resources (interview transcripts, online data, internal documents), and then a knowledge base has been build from it. This was the basis of a complex RAG system, that was evaluated against a golden dataset. Agents have been used to find out the contradicting intelligence, the statements supporting each other, and to store back the generated knowledge.
Used: Python, RAG, LangGraph, LangChain, deepeval, MCP
Franz B.
Last position:
Product Development (AI) at Own initiative
AI telephone assistant platform
Claude Code, Google AI Studio, Python, LLM / Voice-AI, PostgreSQL
- Conception and hands-on development of an AI-supported telephone assistant platform (voice AI / LLM) – from idea and architecture to MVP/product.
- Built agentic workflows and full automations with Claude Code and Google AI Studio.
- Also delivered AI-supported work in client engagements: used Claude Code for governance documentation, requirement drafts, and automations.
Florian B.
Last position:
Project Management / PMO Consultant
PMO & Project Organization Blueprint for Restructuring
Renewable Energy / Solar Equipment
Technologies / Methods: PMO setup, KPI tracking, project organization, Jira, Confluence
- Developed measures to improve management control during a restruct...
Ajay Kumar D.
Last position:
Senior BI and Analytics Engineer at Novartis
- Led enterprise reporting modernization by migrating legacy SSRS reporting solutions to Power BI, supporting 500+ business users while ensuring full GDPR/DSGVO compliance.
- Designed and optimized Power BI and Microsoft Fabric semantic models using star schema, dimensional modeling, advanced DAX, and performance optimization techniques, reducing query latency by 25%.
- Delivered 20+ executive and operational dashboards featuring KPI scorecards, drill-through, bookmarks, and row-level security, improving reporting efficiency by 20%.
- Enabled self-service analytics through governed Power BI datasets, dataflows, and gateway architecture, increasing business-led reporting adoption by 35%.
- Configured an incremental refresh policy and query folding for a 50+ million row sales dataset, reducing daily report refresh times by 85%.
- Deployed automated ETL/ELT pipelines using Azure Data Factory, Microsoft Fabric, and Snowflake, reducing reporting delivery timelines by 40% through workflow automation.
- Spearheaded Microsoft Fabric analytics modernization initiatives including lakehouse architecture, OneLake integration, and centralized data platform development, reducing data latency from 2 hours to 20 minutes.
- Translated business requirements from 15+ stakeholders into scalable Power BI semantic models and dashboards, improving reporting consistency and reducing ad-hoc reporting requests by 25%.
- Applied Microsoft Copilot and generative AI tools to accelerate SQL development, DAX authoring, technical documentation, and testing activities, reducing development effort by approximately 15 hours per week.
Vera S.
Last position:
Founder & Independent Consultant at VS Consulting
- Transformed the marketing department of a global logistics and transport manufacturer in Germany, identifying value-driving measures, coordinating key stakeholders like CMO and CSO, and designing and implementing revenue-driving initiatives.
- Led a strategic transformation & change-management and implementation project for the CMO and CPO of a KKR portfolio company (HQ in NYC & Geneva), optimizing PMO structures, designing and leading executive workshops, managing executive stakeholders, and reporting across key global markets.
- Identified and quantified growth and cost-cutting opportunities for a global F&B/FMCG manufacturer & distributor through market sizing, competitive analysis, and profitability assessments, highlighting €300 m e-commerce growth potential and €100 m savings.
- Directed internal communications and PMO for an enterprise-wide analytics initiative at a global pharma company, creating executive-ready packs, newsletters, and storylines for leadership, while maintaining RAID/critical path and aligning 10+ workstreams across regions.
- Designed and directed a national go-to-market marketing strategy covering customer segmentation, digital/offline touchpoints, and e-commerce journeys for the German commercial lead of a new therapy at a global pharma corporation, earning ‘lighthouse project’ recognition by the country CEO.
- Led a project and team for the board of a DAX-40 company in a comprehensive organizational transformation strategy, managing scopes, budgets, timelines, and stakeholders to deliver a strategy affecting over 100,000 employees globally.
- Upgraded reporting and organizational structure for an automotive e-commerce marketplace, driving operational efficiency and supporting €615 m annual revenue.
Asma K.
Last position:
Data & AI Product Manager – Business & Sales Operations at PUMA GROUP
- Defined the vision, strategy, and roadmap of AI-powered analytics products, ensuring they met the business needs of Sales, Marketing, Finance, and executive teams across Europe.
- Collected business requirements, prioritized AI product features, and led Agile development of forecasting and analytics solutions. Defined product specifications, user stories, and acceptance criteria to ensure successful delivery.
- Collaborated with business stakeholders, Product Owners, data scientists, ML engineers and software engineers to transform AI models into scalable business products and integrate AI insights into operational workflows.
- Designed and implemented Generative AI solutions leveraging Large Language Models (LLMs) to automate reporting and enable natural-language querying of enterprise data, reducing manual effort by approximately 30%.
- Defined product goals and success metrics, tracked product performance and user adoption, and continuously improved the product based on user feedback and business results.
- Established data governance, master data quality and reporting standards across SQL, BigQuery and Power BI environments to ensure reliable, secure and scalable analytics.
Alyosh A.
Last position:
Business Intelligence Consultant at Large Private Equity Group
- Business intelligence and KPI specification and playbook for 35 European companies.
Eduard D.
Last position:
Guest Lecturer at Politehnica University Bucharest
"Reasoning Models: From LLM Foundations to NOC Automation."
Jürgen H.
Last position:
Consultant at NDA
GenAI – Chat & Voicebot
Setup of a GenAI solution with a knowledge base as well as chat and voicebots.
- Definition of use cases and chat/voicebot functionalities
- Project setup for cloud, knowledge base, LLMs and RAG
- AI guardrails, IAM concept
- Governance, Risk & Compliance (GRC)
Result:
Setup of an enterprise GenAI solution with knowledge base, chat/voicebots, IAM and governance.
Andreas A.
Last position:
AI Consultant & Digital Architect at TeamIntel
- Governed multi-agent orchestration for regulated, EU-based companies – self-hostable, compliant with the EU AI Act and GDPR („by design“), BYOM (own models/GPU).
- Two-gate governance: agent deliberation + mandatory human approval, complete signed audit trail; graduated autonomy model („internal → autonomous per skill“).
- Verified knowledge graph („Company Brain“) with source evidence for each answer; proprietary orchestration framework (Virtual Team Framework).
- Industry solutions for financial services: compliance monitoring, invoice and contract review; hands-on development with LLMs (including Anthropic/Claude), agentic workflows, RAG.
- Development of the governance-focused multi-agent platform TeamIntel (see AI reference projects).
Discover over 15,000 top freelancers
Statistics of experts using Generative AI
Aggregated from the professional profiles of matched freelancers.
Experience
18 years (Germany: 16 years)

Position duration
2.2 years (Germany: 2.3 years)

Positions per freelancer
12 (Germany: 10)

Top business areas
Information Technology, Product Development, Project Management

Top industries
Information Technology, Automotive, Professional Services

Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
98% (Germany: 96%)
Master's degree or higher
79% (Germany: 75%)
Doctorate
25% (Germany: 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 Munich 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.
Average rates of experts in Munich 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 (91%)
- Automotive (55%)
- Professional Services (54%)
- Banking and Finance (52%)
- Manufacturing (48%)
- Education (46%)
- Retail (37%)
- Energy (32%)
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 learned patterns in text, images, audio, video and code. It can power conversational assistants, document workflows, content tools, search experiences and creative applications. Unlike traditional automation, it produces adaptable outputs from natural-language instructions.
Models and Methods
Projects may use large language models, multimodal models, embedding models or image-generation systems. Professionals work with prompting, fine-tuning, retrieval-augmented generation, structured outputs and evaluation. They choose between hosted APIs, open-source foundation models and private deployments according to data, latency and control needs.
Building the AI Stack
The ecosystem includes model providers, vector databases, orchestration frameworks, data pipelines, API layers and observability tools. Strong implementation connects these parts rather than treating a model as a complete product.
- Prepare and govern training or retrieval data
- Connect models to company knowledge and business systems
- Add evaluation, monitoring, guardrails and human review
- Deploy secure applications with predictable response quality
Where Companies Use It
Companies use Generative AI for support assistants, sales enablement, internal knowledge search, contract analysis, software tools and personalized content. It also supports research, product design and media workflows. In Munich, teams across manufacturing, mobility, finance, healthcare and technology may need solutions that fit established systems and multilingual users.
When Freelance Expertise Helps
Freelance professionals are useful when a team needs to validate a use case, move a prototype into production or connect models with sensitive business data. They can also strengthen an existing team during model selection, prompt evaluation, data preparation or rollout. Remote collaboration often works well, while on-site work in Munich can help with workshops, process discovery and stakeholder alignment.
- Outputs vary or cannot be traced to reliable sources
- A prototype lacks security, evaluation or monitoring
- Internal data is difficult to retrieve safely
- Adoption requires workflow and user experience changes
What Strong Professionals Bring
Strong Generative AI professionals combine model knowledge with software delivery, data quality, security and product thinking. They define success criteria before selecting a model, test failure cases and make uncertainty visible. They understand token limits, retrieval quality, prompt injection, privacy and cost control, and they document decisions so teams can operate the system after handover.
Frequently asked questions
Questions about Generative AI? Start with the answers below.
Generative AI is used to create text, images, code, audio and other content from instructions or business data. Companies apply it to assistants, knowledge search, document processing, customer support, research and content workflows.
Generative AI produces new content, while many traditional machine-learning systems classify inputs, predict values or detect patterns. The right choice depends on whether the project needs open-ended generation or a narrowly defined prediction.
Generative AI projects often start with a hosted LLM API for rapid testing and broad model capability. An open-source foundation model may be preferable when deployment control, data residency, customization or operating independence matters more than simplicity.
Generative AI work benefits from skills in software architecture, data engineering, cloud infrastructure, information security and user experience. Retrieval design, vector search, evaluation, prompt engineering and API integration are also important for production systems.
Generative AI experience should match the project risk rather than its label. A simple prototype may need focused model and integration knowledge, while a production system handling sensitive data requires proven skills in evaluation, security, monitoring and operational handover.
Generative AI projects can usually be delivered remotely when data access, documentation and communication are well organized. On-site sessions in Munich can add value for discovery workshops, regulated workflows, stakeholder alignment and collaboration with teams that expect German-language communication.
Generative AI professionals should explain model choices, data boundaries, evaluation methods and known failure modes in clear terms. Ask how they handle hallucinations, prompt injection, privacy, monitoring and human review, then examine whether their proposed tests reflect real user tasks.
Generative AI briefs should define the users, workflow, source data, desired outputs and business decision the system supports. They should also state security constraints, integration needs, evaluation criteria and whether the goal is a prototype, pilot or production service.
The average hourly rate of freelancers in Munich, Germany who have used Generative AI in their recent projects is 105 €, which corresponds to a daily rate of about 838 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Generative AI in their recent projects, 98% hold at least a Bachelor's degree, 79% hold at least a Master's degree, and 25% hold a doctorate.
On average, freelancers in Munich, Germany who have used Generative AI in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 2.2 years.
The most common languages among freelancers in Munich, Germany who have used Generative AI in their recent projects are English (98%), German (95%), and French (22%).
The most common industries among freelancers in Munich, Germany who have used Generative AI in their recent projects are Information Technology (91%), Automotive (55%), and Professional Services (54%).
The most common business areas among freelancers in Munich, Germany who have used Generative AI in their recent projects are Information Technology (92%), Product Development (88%), and Project Management (69%).
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.
Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
Would you rather directly get in touch?
We always have the time for a call or email!

Berlin
Hamburg
Cologne
Frankfurt
Stuttgart
Dusseldorf
Dortmund
Essen
Nuremberg