GPT Expert
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Meet FRATCH Experts who have recently used GPT
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)
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
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
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.
Sabine P.
Last position:
AI Consultant at 2coach
The consultancy is developing AI agents for managers for a client. The underlying logic is built in GPTs, while the client works with Microsoft.
In progress:
- Designing and implementing agents for people management and leadership development in Copilot Studio
- Transferring the GPT logic to the end client's Microsoft environment
Michael R.
Last position:
Project Manager at Payone GmbH (Worldline AG)
- Goal/Motivation: PAYONE urgently needs a 360° view of its customers. PAYONE has not had an overarching master data strategy so far. It is not possible to identify customers across all relevant systems.
The organization should be enabled to identify customers across all relevant systems. Establishing the basis for master data management at PAYONE
- Challenge: Due to company acquisitions, the system landscape is very heterogeneous. The company is very dynamic and burdened with many system harmonization and integration projects, meaning resource shortages and changes in project priorities repeatedly make this an almost impossible task.
Due to BaFin findings, the project has a central task and role. The initial focus is on migrating all customers, including their AML/KYC data, from the master-data-leading backend systems to Salesforce. This is intended to resolve one of the largest findings and establish the relevant ODD/EDD processes.
In addition, customer data must be harmonized in Salesforce. Some customers were entered multiple times as a result of earlier migrations. The aim is for only one customer record to remain in Salesforce and for the relevant information from the backend systems to show which products the customer uses and in which processing systems they receive Payone services.
Project: ONE Customer
Budget: 1,5 Mio. €
Team: 10/30 employees (full-time/part-time); 4 vendors/providers
Integration: 8 (subsystems/interfaces)
Applications: Salesforce; SAP S4/HANA; in-house developments
Tools: MS Office; Jira, Confluence, Sharepoint
Methods: Hands-on; Agile (SAFe); Prince2
Jens H.
Last position:
Interim CTO (occasional assignments) at Fujitsu / FSAS
Stabilization of an Azure/.NET landscape in live operation.
- Architecture, DevOps, and operational readiness; technical decisions under time pressure
- Azure DevOps, monitoring, ETL/ELT, cloud security, FinOps, and data-mesh-related topics
Technologies: Azure DevOps, .NET, CI/CD, monitoring, FinOps
Wolfgang T.
Last position:
Overall Project Manager at itzbund
Project overview: The use of “Generative Pretrained Transformer” (GPT) technologies will greatly change the world of work in the coming years. ITZBund is developing a basic service for this purpose, which can be used by its 200 customers. This basic service is offered both on-premises and in the cloud. Launched in 12/23, production systems (based on the MVP) had already been successfully rolled out and operated for several authorities and federal ministries by 05/24.
Project metrics:
- 2024 budget approx. 20 Mio €
- approx. 70 people directly involved in the project
- regular (indirect) contact with approx. 80 people in the wider project environment
My main responsibilities:
- Overall responsibility as external project manager
- Project definition phase/ Project setup and establishment of the project organization
- Strategic and operational project planning, as well as project design and ongoing adjustments
- Ongoing coordination with the project owner and stakeholders at ITZBund
- Ongoing coordination with sub-project managers, agile roles, and other project team members
- Responsibility for project controlling, quality management, risk management, and change management
- Responsibility for providing the basic service in on-premises and cloud environments and its ongoing development
- Planning and leading several hypercare phases
- Collaboration and ongoing coordination with a federal ministry partner project and delivery of an MVP
- Coordination with the agile teams
- Coordination with operations, release, and deployment
- Responsibility for delivering initial customer projects
- Responsibility for developing AI governance
- Ensuring accessibility (BITV)
- Responsibility for setting up a sub-project for marketing activities
- Support in setting up an efficient proposal process
- Stakeholder management
Approach:
- V-Modell XT ITZBund
- Scrum
Tools used:
- Microsoft Office, Skype, MS Project, Confluence, Jira, Sharepoint, Miro
Hans-Dieter G.
Last position:
Training as an AI Expert
I continuously expand my expertise in AI and automation. I work with ChatGPT, OpenAI, Manus, Gemini, MS CoPilot, APIs, LangChain, Hugging Face, Manus, TensorFlow, and Auto-GPT, as well as Python-based ML frameworks and MLOps tools, to intelligently transform traditional software development, analysis, and testing processes.
Huy N.
Last position:
Modern Workplace & Dynamics 365 Consultant at Thinformatics
- Administration and further development of the M365 environment, including Teams, Exchange Online, Intune, and SharePoint Online
- Development of dashboards for performance monitoring with Microsoft Power BI
- Implementation of user requirements and processes with low-code/no-code technologies (Power Apps, Power Automate)
- Use of Jira and Azure DevOps to plan and implement user stories in an agile project context
- Participation in daily stand-ups, sprint planning, sprint reviews, and retrospectives as the technical point of contact
- Planning and implementation of security policies using Azure Conditional Access and multi-factor authentication
- Configuration and deployment of clients and applications via MECM (SCCM) and Baramundi
René P.
Last position:
Full Stack Developer at XPS Software
- Industry: B2B
- Headless frontend with AEM integration
- Special challenge: Migrating a PWA application in live operation based on .NET and legacy code; the entire application must be migrated to React and Express.js/TypeScript
- Technical frameworks: Tailwind, XML, JavaScript, Caddy, ReactJS, Express.js, REST API, JSON
- Cloudflare CDN
- Caddy server with GitHub CI/CD pipeline
Philipp T.
Last position:
Founder & CEO at FRATCH.IO
AI-native B2B SaaS for freelancer sourcing; DACH market.*
Enterprise partnerships across four industries: structured and closed multi-stakeholder deals with Telefónica (Telco), Emma Matratzen (Retail), Nürnberger Versicherungen and Flatex (Financial Services), Hubert Burda Media and Serviceplan Gruppe (Media).
Revenue and growth: scaled FRATCH from €0 to €3.8M annual GMV, with ~80% of revenue sourced from founder-led direct outreach and partner relationships.
Channel partnerships: sold FRATCH as a SaaS solution to recruiting firms (e.g., YER) — built the partner-enabled motion alongside direct enterprise sales.
Team build: scaled FRATCH from solo founder to a team of 7 across engineering, product design, operations, and supply outreach.
Proprietary network asset: onboarded 15,000+ freelancers as registered users — the proprietary DACH network powering FRATCH's matching.
Built and launched FRATCH GPT (fratch.io/gpt): a production conversational AI agent. Architected the full stack — LLM orchestration, embeddings, re-ranking — with hands-on involvement in technical design and execution.
GTM build: owned the full go-to-market stack — outbound, LinkedIn (organic + paid), content, and sales enablement.
Derek M.
Last position:
AI Automations Manager - Hardware Setup, Automation & Voice Agent at Autohaus Mazda
- Setup of new desktop computers
- Setup of a VPS for automation, databases, and chat interface
- Connection to Azure AI Foundry
- Development of various n8n workflows for email, social media, and document management
- Implementation of a QM system (backups, error handling, HITL)
- Setup and optimization of an inbound Voice Agent
Angelika S.
Last position:
Initiator & Lead of the CAMRO Project at CAMRO
- Initiation and management of the CAMRO cooperation platform for municipal animal welfare in Romania
- Conceptualization and development of the web platform, including an interactive map of Romanian counties
- Connecting municipalities and partner organizations in the field of animal welfare
- Development of criteria and transparency standards for participating cooperation partners
Markus O.
Last position:
Lead E-Solution Architect & Senior Requirements Engineer at Zasterbot-Oracle
- Clarification of project objectives, scope and the target business vision for building the AI-based knowledge database.
- Derivation of the initial architecture and implementation strategy for the Zasterbot chatbot, including separation of the MVP and further development stages.
- Development of a target business vision for building a structured knowledge database and integrating a future chatbot.
- Derivation and prioritization of use cases for information retrieval and provision by the chatbot.
- Modeling of data structures and flows for the effective organization of the knowledge database on the Base44 platform.
- Design and implementation of data models for storing and linking relevant information.
- Development of processes for extracting, analyzing and preparing raw data for the knowledge database.
- Ensuring data consistency and quality as the basis for the future chatbot.
- Planning the integration of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) for precise and context-specific answers.
- Implementation of functions for analyzing and displaying data from the knowledge database.
- Use of the Base44 platform with JSON Schema-based entities and a flexible permission concept.
- Implementation of Deno functions for backend logic, event processing and connecting external APIs.
- Integration of OpenAI services for initial data analysis.
Discover over 15,000 top freelancers
Statistics of experts using GPT
Aggregated from the professional profiles of matched freelancers.
Experience
17 years
Position duration
3 years
Positions per freelancer
11
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Professional Services, Banking and Finance
Certification focus areas
Information Technology, Project Management, Product Development
Bachelor's degree or higher
93%
Master's degree or higher
68%
Doctorate
9%
Certifications per freelancer
3
Most common languages
English, German, French
Speak two or more languages
97%
Based on our profile pool as of 5 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 GPT
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 5 Nov 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
GPT 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 (87%)
- Professional Services (51%)
- Banking and Finance (43%)
- Automotive (43%)
- Education (39%)
- Retail (36%)
- Manufacturing (36%)
- Healthcare (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What GPT is
GPT stands for Generative Pre-trained Transformer, a family of language models built to understand and generate natural language. It processes prompts and context to produce text, summaries, structured outputs, classifications and other responses. OpenAI GPT models are widely used as a foundation for business applications, automation and conversational interfaces.
What it builds
GPT supports software that works with language, documents and knowledge. Typical deliverables include:
- Customer support assistants with controlled responses
- Document search and question-answering tools
- Content, translation and summarization workflows
- Data extraction from contracts, tickets and reports
- Internal copilots connected to business systems
Ecosystem and tooling
Strong GPT work combines model APIs with application infrastructure. Professionals commonly work with OpenAI APIs, Azure OpenAI, embeddings, vector databases and retrieval-augmented generation. They also use Python or TypeScript, REST interfaces, orchestration frameworks, evaluation tools, prompt management and observability systems.
When expertise matters
Companies bring in freelance GPT specialists when a prototype must become a dependable product, or when existing automation gives inconsistent results. Expertise is valuable when private documents, customer data, access controls or business-critical decisions are involved. Specialists can also help compare hosted models, open-weight alternatives and the right deployment approach.
Project delivery
A capable professional starts by defining the task, source data, users and acceptable output. They design prompts and retrieval flows, connect GPT to existing services, and create tests for accuracy, safety and failure handling. They should document model limits, review data protection requirements and leave the team with maintainable integrations rather than an isolated demo.
Quality signals
Look for work samples that show measurable evaluation methods without exposing confidential data. Strong professionals explain when GPT can answer, when it should retrieve evidence and when it must hand a task to a person. They distinguish model behavior from application bugs, manage token and latency constraints, protect sensitive information and improve results through structured testing and user feedback.
Frequently asked questions
Not sure where to start with GPT? These answers cover the essentials.
GPT is used to generate and transform language, answer questions, summarize documents, classify requests and extract structured information. Companies also connect it to internal knowledge bases, support systems and workflow automation.
GPT handles varied language and ambiguous requests more flexibly than fixed rules or keyword-based automation. Traditional logic remains better for deterministic calculations, strict validation and processes where every outcome must follow predefined conditions.
A strong GPT professional often combines API integration, Python or TypeScript, data handling and cloud services with prompt design. Retrieval-augmented generation, vector databases, evaluation, security and user experience are also important for production work.
The right level depends on the risk and integration depth of the project. A simple content workflow may need focused implementation skills, while a customer-facing assistant connected to private data requires experience with evaluation, access controls, monitoring and failure handling.
Yes, most GPT work can be handled remotely through shared repositories, documentation, secure environments and regular product reviews. On-site collaboration can help when the project depends on sensitive processes, complex stakeholder workshops or restricted systems.
The best GPT option depends on context length, response quality, latency, privacy needs, integration requirements and operating cost. A qualified professional should compare hosted services such as OpenAI GPT or Azure OpenAI with suitable open-weight models instead of choosing by brand alone.
Ask for a clear evaluation set, defined success criteria and examples of difficult or failed cases. Good GPT implementations cite source material where needed, resist unsafe instructions, protect confidential data and provide a reliable fallback when the model is uncertain.
A GPT freelancer should clarify the users, business outcome, available data, security constraints and systems that must be connected. They should also agree on review responsibilities, deployment ownership, testing methods and how model changes will be monitored over time.
The average hourly rate of freelancers who have used GPT in their recent projects is 98 €, which corresponds to a daily rate of about 783 € based on an 8-hour working day.
Of the freelancers who have used GPT in their recent projects, 93% hold at least a Bachelor's degree, 68% hold at least a Master's degree, and 9% hold a doctorate.
On average, freelancers who have used GPT in their recent projects have 17 years of professional experience, with a single engagement typically lasting around 3 years.
The most common languages among freelancers who have used GPT in their recent projects are English (98%), German (97%), and French (20%).
The most common industries among freelancers who have used GPT in their recent projects are Information Technology (87%), Professional Services (51%), and Banking and Finance (43%).
The most common business areas among freelancers who have used GPT in their recent projects are Information Technology (85%), Product Development (80%), and Project Management (63%).
Main locations of FRATCH Experts, who have recently used GPT
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 
Dusseldorf 
Nuremberg In Austria our freelancers and interim experts support companies from Vienna to Graz — on-site where your project needs them, or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.
Vienna Graz Across Switzerland our specialists are active in Zurich, Geneva, Basel and Bern — working on-site or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.
Zurich Geneva Basel Bern Countries:
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Philipp Thomaschewski
FRATCH CEO
