OpenAI Experts in Stuttgart
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Meet FRATCH Experts in Stuttgart, who have recently used OpenAI
Sercan Tatar
Last position:
Co-Founder & Lead Software Architect at Pflege-Pfad
- Focus: system architecture, cloud-native platforms, microservices, API design
- Product: Pflege-Pfad is a digital matchmaking platform that connects relatives of people in need of care directly with verified care services and caregivers - without an agency and without ongoing fees.
- Business analysis & process design:
- Analysis of the German care market and identification of the key pain points of both target groups.
- Modeling of the core business processes: registration, verification, care request, application, placement, and rating.
- Definition of the business model as a freemium/premium model with optional contact unlocking.
- Creation of user stories and requirements documentation for relatives, care services, and administrators.
- Design of trust and quality assurance mechanisms with document upload, admin review process, and rating system.
- Coordination with stakeholders and validation of product decisions with potential users.
- Technical implementation:
- Design and implementation of the entire platform architecture as a solo developer.
- Design and implementation of a REST API with Spring Boot and Kotlin, including JWT-based authentication.
- Development of the frontend as a single-page application with Angular 17.
- Implementation of the AWS infrastructure with EC2, RDS PostgreSQL, S3, CloudFront, and IAM.
- Document upload with AWS S3 via presigned URLs for verification of care services.
- Email notifications via Resend API.
- AI-supported care service search via OpenAI API.
- Implementation of complete user flows such as registration, login, password reset, and placement process.
- Building an admin panel for user and care service management as well as analytics.
- CI/CD with GitHub Actions and containerized deployments with Docker.
- End-to-end tests with Playwright.
Technologies: Kotlin, Spring Boot 3, Spring Security, JWT, JPA/Hibernate, PostgreSQL, Angular 17, TypeScript, RxJS, AWS (EC2, ECS, S3, CloudFront CDN, RDS PostgreSQL, IAM), nginx, GitHub Actions, Playwright, Maven, Git, OpenAI API, Resend API, Docker, Scrum, i18n (DE/EN/TR), Kiro, feature-flag architecture.
Artyom Narimanyan
Last position:
AI Automation Engineer & Solution Architect at Technology Research Project
Designed and developed an AI-powered automation platform using n8n to analyze social media niches, identify target audiences, and automate marketing strategy generation. The solution combined AI agents, workflow orchestration, and data analysis to automate research processes and generate data-driven insights.
- Designed and implemented complex automation workflows using n8n
- Developed AI-powered analysis agents for market and audience research
- Integrated multiple APIs and AI services into automated workflows
- Built automated market, competitor, and target audience analysis pipelines
- Leveraged Large Language Models (LLMs) for information summarization, classification, and prioritization
- Containerized and deployed the platform using Docker
Technologies: n8n, AI Agents, OpenAI APIs, Prompt Engineering, LLMs, Docker, Linux, REST APIs, Webhooks
Albert Frischmann
Last position:
Lead Product Owner at CMBlu Energy AG
- Lead Product Owner for 4 development teams
- Leading and coordinating a greenfield project with parallel implementation of core components by independent teams; managing dependencies and resources
- Establishing a data lakehouse approach, including analysis of data volumes and future requirements as part of a cloud migration (best-of-breed approach)
- Responsible for requirements analysis, selection, and piloting of a LIMS/ELN system, supported by advising decision-makers and managing external vendors
- Introducing and managing an OpenWeb UI and Azure OpenAI-based RAG system to support knowledge extraction and data-driven analyses
- Setting up, configuring, and managing Jira projects, as well as developing project-specific workflows and automations
- Implementing classic Scrum processes with all ceremonies and taking on the Scrum Master role for all involved teams
- Assisting in hiring through interviews and assessments from a product owner's perspective
- Making key architectural decisions, including selecting the platform for the data lakehouse (Databricks) and the strategic integration of LIMS and analytics platforms
Ronald Foerster
Last position:
IT Consultant & Training at Various Small Projects & AI Training
- Development of multiple websites for small businesses (6)
- SEO/SEM
- Business Consulting (Implementation of ERP systems (Fresha / MS Dynamics))
- AI Tooling, Prompting & Coding
- GenAI Chatbot (GPT 4.0)
- Creation of a telephone agent (NLP services, Twilio, Python, Azure Services)
- Python coding, report & dashboard creation
- Stakeholder management and consulting throughout the project lifecycle
Training and Certifications in AI:
- Microsoft Azure AI Fundamentals
- Develop Gen AI Solutions with Azure Open AI Service
- Designing and Implementing a Microsoft Azure AI Solution
- Artificial Intelligence for the Business Professional
- Generative AI for the Business Professional
- Certified Artificial Intelligence Practitioner
Chaima Dahri
Last position:
Data Scientist Intern at Marelli Automotive Lighting
- Developed and deployed a deep learning model for automated keypoint detection in headlamp light distributions.
- Prepared and processed datasets, and selected VGG16 after benchmarking CNN architectures for the best accuracy efficiency trade-off.
- Delivered a Flask REST API, containerized with Docker, and integrated the solution into an existing internal system, enabling automated and efficient evaluation of headlamp designs.
Andreas Neumann
Last position:
Project Manager at Rundfunk Berlin-Brandenburg rbb / IVZ
- Implementation of a GDPR-compliant knowledge management system "Ylvi" using Microsoft Azure Cloud Services (EU operation)
- Deployment of RAG technology (Retrieval Augmented Generation) and ChatGPT model for a digital coaching service
- Provision of company information: training documents, training videos, intranet content, technical concepts, best-practice processes, change management materials
- Used as an expert system in user support, with key users and end users
- Knowledge transfer on LLMs and RAG
- Research and development of RAG model structure and language model configuration
- Solution architecture, document analysis, test concept for language models, knowledge transfer workshops, content analysis, test concept, system prompt development
- Development control, stakeholder management, change management, implementation, deployment
Marcel Kleber
Last position:
Freelance at Kleber Digital Consulting
Christoph Diefenthal
Last position:
Agentic RAG AI System at Financial Services Provider
- Developed an agentic RAG system to support the development organization.
- Technologies: Python, LangGraph, Qdrant, Claude Code, GitHub.
Discover over 15,000 top freelancers
Statistics of experts using OpenAI
Aggregated from the professional profiles of matched freelancers.
Experience
14 years (Germany: 16 years)
Position duration
1.6 years (Germany: 2.8 years)
Positions per freelancer
14 (Germany: 12)
Top business areas
Information Technology, Product Development, Operations
Top industries
Information Technology, Automotive, Transportation
Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
83% (Germany: 89%)
Master's degree or higher
33% (Germany: 61%)
Certifications per freelancer
5 (Germany: 3)
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 98%)
Based on our profile pool as of 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Stuttgart are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range.
Average rates of experts in Stuttgart using OpenAI
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 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What it covers
OpenAI work usually means using ChatGPT, the OpenAI API, and GPT models to build text, chat, search, and automation features. Teams bring in specialists when they need reliable prompts, structured outputs, and clean integration into real products.
Typical delivery
- Chat and support assistants
- Content drafting and review flows
- Knowledge search and Q&A features
- Workflow automation with tool calls
- Model evaluation and prompt tuning
Ecosystem
Strong professionals know how to combine the OpenAI API with Python or JavaScript, back-end services, vector databases, and cloud tooling. They also understand token limits, response formatting, function calling, and guardrails that keep outputs usable in production.
When to hire
Companies usually look for freelance expertise when internal teams have a prototype that needs hardening, or when a product needs faster delivery than a full hiring cycle allows. In Stuttgart, this is common for software, industrial, and enterprise teams that want local collaboration, but remote work is often fine for API-based projects.
What strong specialists do
- Turn vague use cases into clear model behavior
- Write prompts that hold up under real user input
- Test edge cases, latency, and failure paths
- Add safety checks for sensitive or regulated use
- Document assumptions so teams can maintain the work
Quality signals
Good OpenAI specialists focus on repeatable results, not flashy demos. They can explain why a prompt works, how they measure output quality, and when to use retrieval, fine-tuning, or a simpler rules-based step instead of another model call.
Frequently asked questions
The facts hiring teams ask for most often when it comes to OpenAI.
OpenAI is used to add language features to products and internal tools. Common uses include chat assistants, document summaries, search over company knowledge, and workflow steps that turn unstructured text into structured data. Many teams start with ChatGPT-style interactions and then move to API-based features once the use case is clear.
OpenAI is often chosen for its broad ecosystem, strong tooling, and familiar API patterns. Anthropic and Google Gemini can also be strong options, especially when teams already use those stacks or need a different model profile. A good specialist compares them by output quality, latency, cost, and fit for the task rather than by brand alone.
A strong OpenAI specialist should understand prompt design, API integration, and how to evaluate outputs in real use. Useful adjacent skills include Python or JavaScript, basic back-end work, vector search, and secure handling of company data. For more advanced work, they should also know when to use retrieval, tool use, or structured outputs.
A simple OpenAI prototype may only need a specialist who can wire up the API and shape prompts quickly. A production system needs deeper experience with reliability, cost control, safety checks, and testing. The right level depends on whether you want a proof of concept, an internal tool, or a customer-facing feature.
For many OpenAI projects, remote collaboration works well because most of the work is API-based and easy to review in code and short demos. On-site time can help when the project involves sensitive data, cross-team workshops, or close work with product and compliance teams in Stuttgart. Many companies use a mix of both.
Look for clear test cases, documented prompts, and evidence that the specialist checked real outputs against your use case. A solid OpenAI expert can explain trade-offs, show how they reduced errors, and describe what they would do when the model gives weak or unsafe answers. Good work is measurable and maintainable, not just impressive in a demo.
OpenAI is the vendor and model ecosystem, while ChatGPT is one of its best-known products. Many company projects use the OpenAI API behind the scenes rather than the ChatGPT app itself. A good specialist knows both the product experience and the API layer, because they solve different problems.
For many OpenAI use cases, careful prompting and retrieval are enough. Fine-tuning becomes useful when you need a very consistent style, a narrow task, or repeated output patterns that prompts alone do not hold reliably. A good specialist will first test the simpler option before adding complexity.
The average hourly rate of freelancers in Stuttgart, Germany who have used OpenAI in their recent projects is 97 €, which corresponds to a daily rate of about 776 € based on an 8-hour working day.
Of the freelancers in Stuttgart, Germany who have used OpenAI in their recent projects, 83% hold at least a Bachelor's degree and 33% hold at least a Master's degree.
On average, freelancers in Stuttgart, Germany who have used OpenAI in their recent projects have 14 years of professional experience, with a single engagement typically lasting around 1.6 years.
The most common languages among freelancers in Stuttgart, Germany who have used OpenAI in their recent projects are German (100%), English (100%), and French (25%).
The most common industries among freelancers in Stuttgart, Germany who have used OpenAI in their recent projects are Information Technology (100%), Automotive (75%), and Transportation (63%).
The most common business areas among freelancers in Stuttgart, Germany who have used OpenAI in their recent projects are Information Technology (100%), Product Development (88%), and Operations (75%).
Main locations of FRATCH Experts, who have recently used OpenAI
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 
Dusseldorf 
Dortmund 
Essen 
Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
