AI Agents Experts in Frankfurt
matched in minutes from over 15,000 CVsHire experts who design autonomous workflows, connect large language models to business systems, and deliver reliable agent orchestration. FRATCH matches you quickly and precisely with vetted, available freelancers for your AI Agents project.
Meet FRATCH Experts in Frankfurt, who have recently used AI Agents
Vadim R.
Last position:
Independent AI Product Lab – Agentic Product Owner / Product Builder | R&D
- Hands-on development of AI-native product prototypes with specialized AI agents for research, requirements, business logic, UX/flow design, test case generation and quality assurance.
- Structured use and orchestration of AI agents through clearly defined roles, inputs/outputs and handover points; breaking down complex product tasks into verifiable work packages and iterative prototyping cycles.
- Establishment of human-in-the-loop quality gates to validate AI-generated results for functional correctness, consistency, completeness and feasibility; targeted rework cycles in case of deviations.
- Development of a regulatory GenAI/rules prototype for CRD VI with a structured decision flow, web UI, rule-based validation and automated test cases; iteration of the business logic through to a pilot-ready POC.
- Design of an AI-to-Action banking prototype: AI intent → consent → bank/product logic → conversion including admin console; translating the product idea into MVP scope, role model, user flows and clickable prototypes.
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 mini applications that enable non technical employees to solve business problems independently
- Implementation of internal business applications with Single Sign On (SSO) and Azure PostgreSQL integration on Hetzner Linux servers
- Implementation of nine mini applications with Single Sign On (SSO) and Azure PostgreSQL integration on Hetzner Linux servers
- Techstack: Python, Nextjs, Typescript, Streamlit, Anthropic SDK (Claude), Azure, Linux Ubuntu, PostgreSQL, MS SQL, Angular, Authentik
Ali A.
Last position:
Founder & Architect at Independent AI R&D
- Fully on-premises LLM document-examination platform for a compliance-critical banking domain: agentic LangGraph pipeline with deterministic verification, every AI judgment structured and source-anchored; ~960 automated tests, zero data egress
- GPU throughput engineering (quantized serving, speculative decoding, prefix caching): 9.5x extraction speed-up, 500+ multi-document case files per day on a single A100
- AI-native EDI/EDIFACT integration platform (~116k LOC Java 25 / Spring Boot 4, 1,900+ tests): LLM-drafted partner mappings machine-verified before go-live (DFDL conformance, field-coverage checks, dry runs), ~99.5% byte match on real customer files — replacing weeks of manual mapping per partner
Michael H.
Last position:
Frontend Developer at RTL Tech
- Development and optimization of the RTL+ frontend application for SmartTV and set-top box platforms with React and Next.js.
- Key role in the technical coordination of developers within the team and in coordinating implementation.
- Central interface to adjacent teams to simplify development processes and improve cross-team alignment.
- Improved frontend performance, stability, and rendering behavior on low-powered devices in a restricted runtime environment.
- Implemented a frontend testing strategy with Jest, React Testing Library, and Playwright.
- Implemented accessibility improvements according to WCAG 2.2 and WAI-ARIA.
- Integrated Didomi Consent Management as a contribution to increasing ad monetization on streaming platforms.
- Used AI-supported engineering workflows with Cursor for structured implementation, refactoring, and faster problem solving.
Technologies used: React, Next.js, TypeScript, JavaScript, GraphQL, Apollo Gateway, Zustand, Tailwind CSS, Styled Components, React Testing Library, Playwright, Jest, HTML5, CSS3, AWS Lambda, EC2, CloudFront, S3, GitLab CI/CD, NX, Cursor
Saqib J.
Last position:
AI Developer / AI Engineer (Lead) at KOM4TEC GmbH
- Conceptual design and implementation of modular AI assistants for sales and business processes in the Microsoft ecosystem (Agentic AI, Copilot extensions)
- Frontend architecture and development with React + TypeScript for embedded chat and assistant surfaces (streaming UI, hooks, React Query, OpenAPI clients)
- Enterprise-level agent development: reusable skill/agent library, MCP server, review and compliance gates
- LLM integration into the user experience: Anthropic (Claude), OpenAI, tool use, RAG pipelines, prompt engineering, guardrails
- Architecture and code review consulting as well as mentoring in the AI development team
- Integration with Microsoft Graph, Power Platform, and Azure services
- Technologies: React, TypeScript, Anthropic Claude, OpenAI, MCP, RAG, Microsoft Graph, Power Platform, Azure
Anthony M.
Last position:
Research and Development, AI for Enterprise at Mwanachama
- Built an MCP (Model Context Protocol) layer for Mwanachama's agency service, turning domain manager methods into callable AI-agent tools. This included a composite tool that builds a full organization design (org chart, goals, workflows, RACI matrix) from one specification.
- Built the chat-driven agency builder (Wakala Studio and API), where an organization describes its structure in natural language and an AI agent uses those tools to construct and modify the live design.
- Added an insights service so an organization can review AI-agent interactions and completed work. Insights from that review feed back into solution design, gated by architect and user sign-off.
- Alongside this, designed and built the platform itself: ~20 Go microservices on PostgreSQL, Flutter and React clients, deployed on Kubernetes.
- AI agents scan the platform autonomously for security gaps and run scripted tests, covering API (Postman-style) and UI testing. The rest of the work stays supervised. No rogue agents, promise.
Maxime D.
Last position:
Lead Product Manager E-invoicing & AI at fino data services GmbH
- Responsible for the concept, planning, and implementation of the product development of GetMyInvoices 2.0 and the subcomponent InvoiceRails
- Independent work on all aspects of the project, including concept, specification in tickets, and coordination of developers
- Creation, management, and prioritization of tickets to ensure all tasks are completed on time and with high quality
- Carrying out and/or coordinating tests and ensuring the proper implementation of the developed features and functionalities
- Close collaboration with developers to clarify technical requirements and ensure the implementations match the specifications
- Regular reporting on project progress and documentation of key decisions, changes, and risks
- Taking on the subject matter lead for all topics around e-invoicing and Peppol, especially in relation to the InvoiceRails component
- Internal consulting and knowledge sharing on e-invoicing and Peppol for other teams and departments
- Tracking market trends and new developments in e-invoicing and Peppol to continuously adapt the product strategy
- Ensuring the long-term scalability and flexibility of the products for future technical and regulatory changes in the e-invoicing area
Jan S.
Last position:
Bootcamp Coach at neuefische GmbH
- Bootcamp Coach: "Digital Sales with AI" for neuefische GmbH
- Creation of curriculum and content for career changers seeking to start a career in digital sales
- Teaching of methods and tactics for an exhaustive tech stack:
- AI Agents Zapier and make.com
- AI Tools Midjourney, heygen, Text-Text LLMs (ChatGPT, Claude, Gemini etc.)
- Sales Software Stack: Fireflies, HubSpot, WIX, Talkwalker
Yves S.
Last position:
Owner and AI Operator at Path to AI
- Operational implementation of the growth levers of growing E-Com brands: SEO, GEO, SEA, shop, conversion, and automation of recurring processes.
- Building and managing specialized AI agent systems that work as roles (SEO, content, conversion, Shopify engineering) instead of single prompts.
- Working either as done-for-you execution or as done-with-you setup, where the brand's team can continue working on its own afterward.
- Customers and projects include TeamTex and Original Veddel, Störtebekker, ConstructionX.
- AI workshops and enablement formats for specialist and leadership teams, plus the joint webinar series AI Vibe Club with Xentral.
Noel L.
Last position:
Founder & Lead Engineer at ausbildung-in-der-it.de
- Platform established and running stably; deliberately reducing my involvement to refocus on an engineering mandate in the financial sector.
- Built an own SaaS learning platform from the ground up and scaled it to over 20,000 users (over 6,000 courses sold, B2C and B2B); end-to-end ownership from development through infrastructure to operations.
- Built a lab environment that provisions an isolated Linux container per user (Docker, Traefik, Go), including automatic provisioning and a dedicated subdomain per user.
- Integrated LLM features into the product and accelerated development end-to-end with AI-assisted workflows (Claude Code, Codex); CI/CD with automated tests.
Najat D.
Last position:
Freelance Consultant Microsoft Purview at Bechtlee IT-Systemhaus
- Design and global rollout of sensitivity labels (confidentiality labels) for automated classification and encryption of business-critical data.
- Definition and rollout of Data Loss Prevention (DLP) policies to protect IP and personal data across endpoints, Exchange, SharePoint, Teams, and non-Microsoft clouds.
- Setup of Insider Risk Management policies to detect and contain excessive data leaks and risky user behavior.
- Implementation of GDPR and retention requirements through automated retention policies and structured records management.
- Technical support for legal teams in internal and external investigations using eDiscovery (Standard/Premium) and Content Search.
- Continuous improvement of the security and compliance level by reviewing the Microsoft Compliance Manager and closing gaps (regulations such as ISO 27001, NIS-2)
Almaz A.
Last position:
Head of Innovation AI
In my current position, I have end-to-end responsibility for AI products: from identifying and prioritizing use cases, developing sound business cases, AI roadmaps, and capacity and resource allocation, through to scalable implementation across countries and business areas.
I design operating models, delivery standards, and operational concepts that ensure AI product development runs reliably and scales sustainably – always aligned with strategy, goals, capacities, and business value.
Leading and developing interdisciplinary teams of data science and product professionals in an agile working model is a core part of my role – I currently lead a team of three employees.
I am confident in stakeholder management at senior management level and in international structures, and translate complex technical topics into clear, business-oriented recommendations for action.
I consider governance from the outset: I consistently align AI initiatives with regulatory requirements (including the EU AI Act), risk management, and data protection requirements.
Gregor P.
Last position:
Engineering Data Management Project Manager
Technical and commercial risk assessment for an investment project in the hardware sector (scaling potential, liability risks, operational processes) Process consulting for two SMEs in the engineering environment, focusing on workflow digitization, PLM
Mobin R.
Last position:
Senior Consultant and Chief Product Owner at Luxota Travel Tech
- Coached teams in Agile methodologies and Scrum framework implementation.
- Aligned the product roadmap with business goals such as increasing bookings, improving user experience, and expanding supplier integrations.
- Collaborated with developers and third-party providers to ensure smooth API integration and end-to-end functionality.
- Created and continuously refined the product backlog with user stories, bugs, and technical improvements.
- Prioritized backlog items based on business value, revenue impact, and regulatory deadlines.
- Worked closely with backend and frontend teams to clarify dependencies and prioritize technical debt.
Hamid M.
Last position:
Head of Operations at transact – AI-native company intelligence
Responsible for operations build-up and scaling
Defining the global digital strategy and roadmap
Acting as product owner for the AI applications
Developing and maintaining strategic networks to support customers’ change
Responsible for custom projects and change management
Product owner for an AI native application that shortens research cycles from 2 weeks to 1-2 days
Introduced an AI agent to optimize company and market analysis processes
Established strategic partnerships with major data and technology incumbents
Delivered dedicated customer projects in scope, time and budget
Discover over 15,000 top freelancers
Statistics of experts using AI Agents
Aggregated from the professional profiles of matched freelancers.
Experience
14 years (Germany: 15 years)
Position duration
1.7 years (Germany: 2.8 years)
Positions per freelancer
9 (Germany: 10)
Top business areas
Product Development, Information Technology, Project Management
Top industries
Information Technology, Banking and Finance, Education
Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
100% (Germany: 96%)
Master's degree or higher
65% (Germany: 71%)
Doctorate
12% (Germany: 14%)
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 96%)
Based on our profile pool as of 19 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Frankfurt 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 Frankfurt using AI Agents
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 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
AI Agents 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 (83%)
- Banking and Finance (56%)
- Education (44%)
- Media and Entertainment (39%)
- Retail (33%)
- Professional Services (28%)
- Advertising (22%)
- Automotive (22%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What AI Agents Are
AI Agents are software systems that use language models, tools and defined goals to plan and complete tasks. Unlike a single prompt-and-response chatbot, an agent can decide which action to take, call APIs, retrieve information and continue until a workflow reaches a useful result. Agentic AI is commonly used for assistants, automation and decision support.
What They Build
Companies use AI Agents to connect natural-language interfaces with real business processes. Typical deliverables include:
- Customer support agents that search knowledge bases and route complex cases
- Research agents that gather, compare and summarise information
- Sales and operations assistants connected to CRM and ERP systems
- Document workflows for extraction, review and approval
- Internal copilots for teams working with company data
Ecosystem And Tooling
Strong professionals work across model providers such as OpenAI, Anthropic and Google, while selecting frameworks that fit the workflow. Common components include LangChain, LangGraph, LlamaIndex, vector databases, retrieval-augmented generation and structured tool calling. They also connect REST APIs, message queues, observability tools and cloud services.
When Expertise Helps
Freelance expertise is valuable when a prototype must become a dependable product or when internal teams lack agentic AI experience. Companies often need support with system design, prompt and tool boundaries, data access, evaluation and production rollout. In Frankfurt, this can suit financial, logistics, industrial and professional-services teams, with remote work or on-site collaboration depending on security and workshop needs.
Reliable Agent Design
Good AI Agents are not judged by fluent answers alone. Specialists define clear responsibilities, constrain tool access, handle uncertainty and protect sensitive data. They create evaluation sets, trace agent decisions, test failure paths and add human approval where an automated action could cause harm.
Choosing A Specialist
Look for professionals who can show complete workflows rather than isolated demos. Ask how they measure retrieval quality, prevent prompt injection, manage model changes and control operating costs. Adjacent skills in backend integration, data engineering, cloud security and product discovery help turn an agent into a maintainable business capability.
Frequently asked questions
Before you brief your next project: the most common questions about AI Agents.
AI Agents are used to handle multi-step tasks that require reasoning, information retrieval and actions in connected systems. Examples include support triage, document processing, research, scheduling and internal knowledge assistance.
AI Agents can choose tools and sequence actions based on a goal, while a conventional chatbot mainly returns prepared or generated replies. Traditional automation follows fixed rules, whereas an agent can handle more variation but needs stronger controls, testing and supervision.
Agentic AI projects benefit from backend integration, API design, data pipelines, cloud security and user-experience research. Knowledge of retrieval-augmented generation, vector databases, evaluation methods and observability is also important for production work.
AI Agents require a level of expertise that matches the risk and complexity of the workflow. A simple internal prototype may need focused model and integration knowledge, while customer-facing or regulated systems call for proven testing, security, monitoring and human-approval practices.
AI Agents projects often work well remotely because design, coding, evaluation and documentation can be handled online. On-site workshops in Frankfurt can still help with process discovery, stakeholder alignment and access discussions, especially for sensitive business systems.
AI Agents professionals should explain how they control tool permissions, protect data, evaluate outputs and respond to model failures. Ask for evidence of a tested workflow, clear monitoring plans and practical limits on what the agent is allowed to do.
Agentic AI is useful when inputs are varied, decisions depend on context and the system must select among several tools. A workflow engine is usually better for deterministic processes with stable rules, and many strong solutions combine both approaches.
LLM agents need more than prompt writing. Professionals should clarify the business goal, available data, permissions, success criteria, escalation paths and expected collaboration model before choosing models, frameworks or deployment architecture.
The average hourly rate of freelancers in Frankfurt, Germany who have used AI Agents in their recent projects is 112 €, which corresponds to a daily rate of about 897 € based on an 8-hour working day.
Of the freelancers in Frankfurt, Germany who have used AI Agents in their recent projects, 100% hold at least a Bachelor's degree, 65% hold at least a Master's degree, and 12% hold a doctorate.
On average, freelancers in Frankfurt, Germany who have used AI Agents in their recent projects have 14 years of professional experience, with a single engagement typically lasting around 1.7 years.
The most common languages among freelancers in Frankfurt, Germany who have used AI Agents in their recent projects are German (100%), English (100%), and French (11%).
The most common industries among freelancers in Frankfurt, Germany who have used AI Agents in their recent projects are Information Technology (83%), Banking and Finance (56%), and Education (44%).
The most common business areas among freelancers in Frankfurt, Germany who have used AI Agents in their recent projects are Product Development (94%), Information Technology (89%), and Project Management (83%).
Main locations of FRATCH Experts, who have recently used AI Agents
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 
Stuttgart 
Dusseldorf 
Essen Countries:
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FRATCH CEO
