FastAPI Experts in Cologne
in minutes from over 15,000 CVs with the power of AIHire experts who build FastAPI services, REST APIs, async endpoints, and OpenAPI documentation with Python and Pydantic. They fit greenfield builds, API refactors, and production hardening, with fast, precise matching to vetted, available freelancers.
Meet FRATCH Experts in Cologne, who have recently used FastAPI
Sophia Wagner
Last position:
AI Engineer & Technical Consultant at Freelance
- Delivered ML pipelines for OCR, semantic search, and computer vision
- Integrated Azure AI Agents and GPT workflows for automation and QA
- Deployed cloud-based FastAPI services with scalable architecture
- Created integration docs and advised on LLM production readiness
Ralph Konitzer
Last position:
Product Owner / Business Owner at AXIS Management Consulting GmbH
- Full product responsibility from a business perspective: requirement analysis, UX design, product strategy, and go-to-market implemented without an internal dev team using fully AI-supported development (Claude Code / Anthropic)
- Technical differentiation: KRITIS-compliant air-gapped deployment (Windows/NSIS), GDT interface for PVS integration, DATEV-LODAS export for payroll
- Managed pilot operation with initial external client (Dormagen medical practice): structured requirement gathering, test support, error analysis, and release management
- Developed rollout and sales strategy for market entry in the segment of private practices and small medical centers
- Human-in-the-Loop development principle: business decision → AI implementation → manual review → approval → release – each sprint documented in Jira (TIME project), every change traceable via co-authored commits
- Product outcome: Tauri/Rust desktop app with GDT watcher, multi-tier model (Starter/Professional/Enterprise), cloud mirror on Hetzner/Traefik, complete ISMS framework based on ISO 27001 and BSI basic protection as product foundation
- Direct method validation for the test manager role: hands-on experience with quality assurance of AI-generated products from a user perspective, review gate discipline, release approval under GDPR and the EU AI Act
Kevin Baßler
Last position:
Procurator and AI Lead at ValueData GmbH
- Serve as AI lead for life-science solutions, integrating advanced AI models directly into company workflows and ensuring seamless deployment.
- Design and implement deep learning architectures (PyTorch, Keras) for complex biomedical challenges, including cell segmentation, multimodal omics analysis, and prediction of point clouds.
- Develop and deploy robust LLM-based systems, including RAG architectures and agentic workflows using LangGraph, to facilitate natural-language interaction with complex medical data.
- Lead cross-functional initiatives to apply foundation models and explainable AI (xAI) to clinical and evolutionary algorithms.
Filipp Trigub
Last position:
Multi-chain LLM copilot for academic teaching and studying at Infolab.ai
- Build a sophisticated AI copilot to augment the students’ learning experience and provide AI-derived insights to professors.
- Build a multi-chain LLM system adapting to user needs at its own accord with a Weaviate vector DB based RAG system and evaluated it with Ragas.
- Build responsive react frontend, and backend systems handling auth, data management and auxiliary services as a RESTful API.
- Deployed and managed the app to the cloud in a production environment including the CICD via multi-stage deployment.
Sabrine Krichen
Last position:
Team Lead at InstaDeep
- Led a team of junior Research Engineers, providing mentorship, technical guidance, and career development support to foster their growth in deep learning and machine learning engineering.
Allal Kharaz
Last position:
Java Senior Full Stack Developer at Insurance ÖRAG
- Further development of a policy administration system (contract/claims) for the legal expenses insurer ÖRAG.
- My role: Senior Software Developer.
- The team consists of 12 developers.
- Technologies used: Java 8/21, Java EE, Quarkus, WebLogic, JPA, RabbitMQ, JTA, CI, CD, Jenkins, DB2, Maven, Jenkins, GIT (bitbucket) later GitLab, Junit, Elasticsearch, Mockito, Jira, SonarQube, Scrum, React, Workflow
- Migration and modernization of legacy systems: rewrote C and C++ code in Java to improve maintainability, scalability, and performance. Refactored Python into Java, including optimization and integration into modern architectures.
- Study on the use of AI (Codex) for implementing a Java feature. The goal is to compare the time spent and productivity of AI-supported development with a classic implementation by a developer. The results should show how strongly the use of AI affects development time and efficiency.
- Development of the following tariff calculators for the years 2024/2026: private, companies, doctors, farmers, owner-occupied G + H, landlords, traffic, club, top managers, sales representatives, special criminal law, savings bank, municipal, BayGT, doctors, Dehoga
Discover over 15,000 top freelancers
Statistics of experts using FastAPI
Aggregated from the professional profiles of matched freelancers.
Experience
12 years
Position duration
1.7 years (Germany: 1.8 years)
Positions per freelancer
7 (Germany: 8)
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Education, Information Technology, Healthcare
Bachelor's degree or higher
100% (Germany: 96%)
Master's degree or higher
80% (Germany: 72%)
Doctorate
20% (Germany: 8%)
Certifications per freelancer
1 (Germany: 2)
Most common languages
German, English, French
Speak two or more languages
83% (Germany: 97%)
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 Cologne 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 Cologne using FastAPI
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
FastAPI for APIs
FastAPI is a Python framework for building APIs with clear request models, validation, and automatic docs. Teams use it for backend services, internal tools, microservices, and data-facing endpoints that need to stay easy to read and easy to extend.
What it fits
- REST APIs for web and mobile products
- Async services that call databases, queues, or external APIs
- OpenAPI-based documentation and client contracts
- Authenticated endpoints for internal systems and partner integrations
Ecosystem
Strong professionals working with FastAPI usually know Python well, plus Pydantic, Starlette, and Uvicorn. They also understand dependency injection, typing, testing, and packaging, so the service is not only fast to write but also stable to maintain.
When companies need help
Companies bring in freelance FastAPI specialists when a new service has to launch quickly, an older API needs cleanup, or async behavior is causing issues. In Cologne, this often fits teams that want a specialist for focused delivery while keeping close coordination with in-house product, backend, and DevOps people.
What strong experts deliver
A good FastAPI expert writes clear endpoints, validates payloads, and keeps the API contract consistent. They set up authentication, error handling, testing, logging, and deployment-ready code so the service can move from prototype to production without rewrites.
How to judge quality
Look for specialists who can explain why they chose a sync or async approach, how they structure dependencies, and how they keep schemas maintainable. Strong FastAPI work is easy to test, documented through OpenAPI, and designed around clean boundaries rather than quick patches.
Frequently asked questions
Key details about FastAPI, drawn from the questions we get asked most.
FastAPI is used to build Python APIs with validation, automatic documentation, and strong support for async work. Companies choose it for backend services, internal tools, microservices, and integration layers that need clean contracts and predictable behavior.
FastAPI is often chosen when teams want typed request models, built-in validation, and automatic OpenAPI docs from the start. Flask is lighter and more manual, while Django is a broader full-stack framework with more built-in structure. FastAPI sits well in the middle when API design and performance matter.
Bring in a FastAPI specialist when a service has to ship quickly, an API needs refactoring, or async behavior has become hard to manage. It also helps when the team wants better schema design, clearer tests, or cleaner integration with Python services and external systems.
A strong FastAPI freelancer usually brings solid Python skills, Pydantic, typing, testing, and API design. Useful adjacent skills include PostgreSQL, SQLAlchemy, OAuth or JWT auth, Docker, and deployment on cloud or container setups.
Not always, but FastAPI work benefits from someone who has shipped real APIs before. Simple CRUD endpoints can be handled quickly, yet production work needs someone who can think about validation, error handling, concurrency, and maintainability from the start.
Yes. FastAPI work is usually well suited to remote collaboration because the main outputs are code, tests, API contracts, and documentation. In Cologne, on-site time only becomes important when a team wants close workshop sessions, architecture alignment, or tight coordination with nearby stakeholders.
Ask how the person structures endpoints, models, and dependencies, and how they test them. Good FastAPI professionals can explain async choices, OpenAPI output, authentication, and error handling in plain words. Their code should be readable, documented, and easy for another specialist to continue.
FastAPI often sits between front-end apps, databases, background workers, and external APIs. It is commonly paired with PostgreSQL, Redis, Celery or other task systems, plus Docker and cloud deployment tooling when the service moves beyond a prototype.
The average hourly rate of freelancers in Cologne, Germany who have used FastAPI in their recent projects is 92 €, which corresponds to a daily rate of about 739 € based on an 8-hour working day.
Of the freelancers in Cologne, Germany who have used FastAPI in their recent projects, 100% hold at least a Bachelor's degree, 80% hold at least a Master's degree, and 20% hold a doctorate.
On average, freelancers in Cologne, Germany who have used FastAPI in their recent projects have 12 years of professional experience, with a single engagement typically lasting around 1.7 years.
The most common languages among freelancers in Cologne, Germany who have used FastAPI in their recent projects are German (100%), English (83%), and French (50%).
The most common industries among freelancers in Cologne, Germany who have used FastAPI in their recent projects are Education (83%), Information Technology (83%), and Healthcare (50%).
The most common business areas among freelancers in Cologne, Germany who have used FastAPI in their recent projects are Information Technology (100%), Product Development (100%), and Business Intelligence (50%).
Main locations of FRATCH Experts, who have recently used FastAPI
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.
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