Generative AI Experts
to build intelligent products with vetted and available freelancers matched in minutesHire experts who design LLM applications, retrieval-augmented generation systems and production-ready AI workflows. FRATCH connects you with vetted, available freelancers whose skills match your Generative AI project precisely and quickly.
Meet FRATCH Experts who have recently used Generative AI
Thomas K.
Last position:
Founder at PentaVision by Thomas Kreutle
Part-time, full-time operations planned from 01/2027
Management consulting for automation, digitalization, interoperability, track & trace and artificial intelligence · Pharma/MedTech and mechanical engineering
- Built a service portfolio across the five competencies: from analysis, architecture and planning to supported implementation.
- Listed as a consultant by BAFA (09/2026): consulting services for SMEs as part of BAFA funding.
- Established a brand identity, website and quality management handbook as the basis for consistent, transparent consulting quality.
Borja C.
Last position:
Independent Transformation and Technology Initiatives at Grey Bear Consulting
Business development and professional exchange
- Developed a consulting offer for digital transformation, AI adoption, and Operating Models; built industry and partner relationships.
Denis K.
Last position:
Interim Lead Digital Platform & Marketing at German Dynamic Drone Center GmbH
- Designed and developed the central company platform LINK: tasks, CMS, shop, academy, image database, fleet records, and AI assistant in a shared data model on PostgreSQL.
- Supported the transformation of established standalone solutions into a cloud architecture; analyzed the existing data landscape and migrated it step by step.
- Integrated internal and external data sources via APIs and webhooks: Microsoft 365, shop with accounting integration, and manufacturer data.
- Implemented an AI assistant for knowledge access and document analysis, including an approval process before sending.
- Migrated and rebuilt a 49-page website with SEO in mind; launched data-driven tools (Drone Finder, Permit Finder) and lead forms.
- Served as the link between management, operations, and IT: analyzed processes on-site, translated requirements into technical solutions, and trained a team with little digital experience using real work.
Udo S.
Last position:
EMEA Sales Manager for AI and Data Infrastructure at PingCAP
TiDB, distributed open-source SQL database; sole sales responsibility, first salesperson for Southern Europe and Benelux; fixed-term contract, like the rest of the EMEA team
- Achieved 153% of a $1.2M ARR target in the first year; the only one of five EMEA AEs above 100%; built a $10M pipeline independently; won Fortune 100 customers within three months—the fastest new customer win by a new hire in PingCAP history
- Won new customers through direct outreach: global French investment bank ($800,000 ARR, five-year contract, 14-month sales cycle with business teams, IT and procurement), Orange, Veepee, Merck Group and OVHcloud; expanded existing Engie account
- Coached SDR, pre-sales and AE colleagues without formal people-management responsibility, especially on complex deals; developed an account and opportunity radar with pre-sales that was adopted company-wide
Abdulrahman S.
Last position:
Senior Business Intelligence Analyst at ELEMENT Insurance AG
- AI-Enabled Analytics & Reporting: Lead a 2-person BI team, applying predictive analytics and automation to translate complex business requirements into forward-looking insights, recommendations, and financial reports.
- Advanced Data Visualization: Design and maintain 25+ high-impact Power BI/Tableau dashboards tracking company-wide KPIs and trends, structured to support predictive and automated reporting.
- Web Analytics & Insights: Own GA4 tracking and analysis, driving a 15% increase in conversion insight through deeper customer journey analysis.
- Data Pipeline Optimization: Partner with data engineers to redesign and automate data pipeline workflows, cutting manual reporting time by 20% while safeguarding data accuracy and system uptime.
Dirk R.
Last position:
Chief Technology Officer at HYPE Softwaretechnik GmbH
Member of the leadership team
40 people across several international sites in my teams.
Technical ownership of the shareholder's buy-and-build strategy: assessment of target companies and their subsequent integration.
Platform, cloud infrastructure, information security and the engineering organisation.
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
Eduard D.
Last position:
Guest Lecturer at Politehnica University Bucharest
"Reasoning Models: From LLM Foundations to NOC Automation."
Andre S.
Last position:
Product Owner at Thinking Networks
- Owned Qvantum, a cloud-based planning platform for personnel, cost center and sales planning
- Managed roadmap, prioritization and stakeholder communication
- Worked closely with development teams and business stakeholders
- Improved usability and supported data-driven decision making
- Led product development initiatives from discovery through delivery
Jan-David B.
Last position:
Founder & Managing Director at Aiverybuddy
AI Consulting | AI Training | Public Sector
Building a specialized AI consulting firm focused on the public sector and the organizational integration of generative AI.
- Development of AI-supported assistant and agent solutions for public sector organizations
- AI consulting, with a focus on public companies
- AI seminars and webinars for the public sector
Alexander H.
Last position:
Senior Product & Strategy Consultant at hegehofer.consulting
Design, development, and market launch of digital products and platforms – from strategic alignment and agile implementation to Go-to-Market and Go-Live, integrating AI into processes and products
Thorsten B.
Last position:
Platform Product Manager at Elia Group / 50Hertz Transmission GmbH
Sovereign, cloud-native developer platform based on Kubernetes for critical energy infrastructure; around 200 people and 15 product teams.
- Introduced the product operating model for the platform, aligning around 18 product managers and product owners with Platform Architecture and Delivery in a matrix organisation.
- Defined the platform product processes and core product artefacts as the standard across all product teams.
- Established processes for non-functional requirements and Requests for Enhancement from consuming teams and customers.
- Designed the Jira structure supporting the programme's product and delivery processes.
Christopher V.
Last position:
Manager AI & Innovation | Digital Transformation | Communications at Deutscher Golf Verband e.V.
I am responsible for developing and implementing AI, innovation and digitalization initiatives at the German Golf Association. My focus is on developing digital products, identifying new technologies and successfully connecting strategy, communications and innovation.
I work closely with the executive board, specialist departments, the communications department as well as external agencies and technology partners, and support projects from the initial idea through to successful implementation.
Highlights:
- Strategic co-responsibility for the relaunch of golf.de, Germany's leading digital platform in golf
- Development and implementation of the German Golf Association's AI strategy
- Development of new AI-supported products and digital services for golf clubs, coaches and golfers
- Management of innovation and transformation projects
- Close collaboration with communications and press relations on future-focused and innovation topics
- Design and delivery of workshops, presentations and AI training sessions
- Management of external software, digital and technology partners
- Preparation of strategic concepts and decision papers for the executive board and management committees
Focus areas: Digital Product Development, AI & Innovation, Digital Transformation, Marketing, Corporate Communications, Public Relations, Business Development, Stakeholder Management
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.
Julian L.
Last position:
Director Group B2B at Allegro
Responsible for the B2B business of Poland's largest e-commerce platform, including full P&L and product direction.
- Full P&L ownership for the B2B Group, responsible for 7bn PLN (~€1.6bn) in annual GMV
- Initiated and lead the business and product group transformation and strategy change to focus on SME customers, leading to a 100% increase in GMV growth (from 12% to 24% YoY)
- Drove AI-based process automation to 48% of B2B Group processes
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 6 Nov 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology 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 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 6 Nov 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 (48%)
- 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 text, images, audio, video and software output from learned patterns. Companies use GenAI to power assistants, search experiences, content workflows, document analysis and creative tools. Unlike conventional automation, it can respond to open-ended requests while still requiring careful controls for accuracy, safety and traceability.
Models and architecture
Projects may use large language models, multimodal models or image-generation systems from providers such as OpenAI, Anthropic, Google and open-source communities. Strong solutions connect models to business data through embeddings, vector databases and retrieval-augmented generation. The architecture also covers prompt design, model selection, context handling, fine-tuning, tool calling and structured output.
Delivery and tooling
Generative AI work spans experimentation, integration and production operations. Specialists commonly work with Python, TypeScript, REST APIs, orchestration frameworks, cloud services, data pipelines and evaluation tooling. They establish versioned prompts, reusable components, observability and safeguards rather than treating a model endpoint as a complete product.
Where companies use it
- Internal knowledge assistants grounded in company documents
- Customer support systems with controlled access to business data
- Contract, invoice and report extraction with human review
- Marketing, product and media workflows with brand controls
- Coding, testing and research support tools
Generative AI can support many industries, from financial services and healthcare to manufacturing, retail and public-sector operations. The right design depends on data sensitivity, response risk, user expectations and the level of human oversight required.
When freelance expertise helps
Companies often bring in freelance specialists when they need to validate a use case, connect a model to proprietary information or move a promising prototype into reliable production. They may also need support with model evaluations, latency, cost control, access policies or migration between providers. A specialist is especially useful when internal teams lack experience with GenAI failure modes and governance.
What strong professionals bring
Experienced Generative AI professionals define measurable quality criteria before selecting a model. They test factuality, relevance, refusal behavior, data leakage and robustness against adversarial input. They understand both product delivery and the limits of foundation models, communicate trade-offs clearly and design systems that keep people involved where automated output carries material risk.
Frequently asked questions
Not sure where to start with Generative AI? These answers cover the essentials.
Generative AI is used to create or transform text, images, audio, video and software output. Common applications include knowledge assistants, document processing, customer support, content production and research workflows. The best use cases have clear data boundaries and a way to review or measure the output.
Generative AI handles open-ended language and media tasks, while traditional automation follows predefined rules and produces more predictable results. GenAI is useful when inputs vary or the required response is difficult to encode as fixed logic. It also introduces risks such as hallucinations, inconsistent wording and privacy exposure, so it often works best alongside deterministic controls.
Generative AI projects do not always need the largest available large language model. A smaller model, retrieval system, classifier or conventional machine learning method may be better for a narrow task, strict latency requirement or sensitive environment. A capable specialist compares quality, context needs, deployment constraints and operating effort before recommending a model.
A strong Generative AI specialist often combines prompt and evaluation design with data engineering, API integration, cloud architecture and security practices. Useful adjacent knowledge includes vector databases, embeddings, retrieval-augmented generation, model observability and user-experience design. Familiarity with Python or TypeScript is common, but the required stack depends on the product.
The right level for Generative AI depends on the risk and scope of the work. A simple prototype may need focused model integration, while a production system handling private data requires experience with evaluations, access controls, monitoring and failure recovery. Ask candidates to explain comparable deliverables and the trade-offs they made, not only the models they have used.
Generative AI work is often suitable for remote collaboration because model APIs, code, evaluations and documentation can be shared securely online. On-site work may add value when specialists must understand sensitive processes, coordinate closely with operational teams or work with restricted infrastructure. Agree early on data access, communication routines and language expectations.
A reliable Generative AI solution should be tested against representative tasks rather than judged by a compelling demo. Review factuality, relevance, safety, response time, data handling and behavior on unclear or adversarial requests. Strong professionals document evaluation methods, known limits, human review points and how quality will be monitored after launch.
Before starting a Generative AI engagement, clarify the target users, source data, model constraints, success criteria and responsibility for reviewing output. Ask whether the project needs retrieval, fine-tuning, tool use, multimodal input or a simple API integration. It is also important to understand privacy requirements, deployment ownership and how changes to a provider's model will be handled.
The average hourly rate of freelancers 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 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 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 who have used Generative AI in their recent projects are English (98%), German (97%), and French (21%).
The most common industries among freelancers who have used Generative AI in their recent projects are Information Technology (89%), Professional Services (48%), and Automotive (40%).
The most common business areas among freelancers 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 all over Germany — available on-site in Berlin, Hamburg, Munich and every major business hub, or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.
Berlin 
Hamburg 
Munich 
Cologne 
Frankfurt 
Stuttgart 
Dusseldorf 
Dortmund 
Essen 
Nuremberg 
Vienna 
Zurich Countries:
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FRATCH CEO
