AI Agents Experts in Frankfurt
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Meet FRATCH Experts in Frankfurt, who have recently used AI Agents
Ali Aminian
Last position:
Platform Engineer & Software Architect at Yatta GmbH
- Architected the Yatta Integration Layer – a config-driven integration platform on Java 25, Spring Boot 4 (WebFlux), Temporal, gRPC and Kafka, enabling new third-party integrations (e.g. AVS fulfillment) via declarative JSON configs with zero code changes.
- Designed and implemented Tink integration with 0Auth IBAN verification to enhance fraud prevention and account validation workflows with Adyen payByBank.
- Architected and implemented an OpenFGA-based authorization model for centralized management of users, groups, and fine-grained access control in the vendor portal.
- Architected and led delivery of the Yatta API Gateway platform using GraphQL Federation, providing a unified enterprise API layer across distributed microservices with centralized authentication, authorization and request orchestration.
- Replaced NGINX + NLB with Istio service mesh and AWS ALB; rolled out WAF, OAuth (Cognito), IP whitelisting and RBAC across environments.
- Migrated CDC from Confluent Cloud connectors to a self-hosted Kafka Connect + Debezium stack, reducing operational cost by ~80% across multiple environments.
- Implemented the Transactional Outbox pattern with Debezium for reliable, exactly-once event publishing to Kafka with Avro and Schema Registry.
- Migrated dunning/payment-recovery workflows from Airflow to Temporal, achieving 99.9% reliability for settlement handling.
- Optimised Apache Airflow with deferrable sensors to handle 1000+ concurrent DAG runs without scaling the worker pool.
- Refactored a monolithic Terraform codebase into 3 modular projects, cutting deployment time by ~45%.
- Stood up full observability with OpenTelemetry, Tempo, Prometheus and Loki; automated dev/staging/prod with ArgoCD, Image Updater and Helm.
- Collaborated with product, operations and engineering stakeholders to define scalable platform architecture and integration standards aligned with long-term business and operational goals.
Saqib Javed
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
Maxime Djongoue
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 Sammeck
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 Schleich
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 Lang
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 Diamante
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)
Gregor Pestsov
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 Rupani
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 Manesh
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
Helge Steimann
Last position:
Partner & Co-Founder at Digitice.io
- End-to-end responsibility for product strategy, technology architecture across multiple client engagements
- Led strategic platform transformations from legacy and on-premise setups to cloud-native architectures on Google Cloud and Azure
- Established SaaS-ready, API-driven platform foundations to support scalability, international rollout and long-term growth
- Designed and implemented AI-enabled platform capabilities, including agentic AI in software development workflows and AI-based automation replacing classical middleware solutions
- Built and led cross-functional product, engineering and technology teams; aligned stakeholders across business, product and technology
Muhammad Arslan
Last position:
Sr. Software Engineer at Hoja AI
- Built scalable Flutter apps (mobile & web) using BLOC and Clean Architecture, improving app performance and maintainability.
- Delivered advanced AI & agentic AI features with real-time communication and personalized user flows.
- Developed backend services in Ktor (Kotlin) and ensured quality via testing, CI/CD, code reviews, and Scrum practices.
John Krämer
Last position:
Vice President, Board Staff at Helaba, Landesbank Hessen Thüringen
Discover over 15,000 top freelancers
Statistics of experts using AI Agents
Aggregated from the professional profiles of matched freelancers.
Experience
15 years
Position duration
2 years (Germany: 2.9 years)
Positions per freelancer
9 (Germany: 10)
Top business areas
Product Development, Project Management, Information Technology
Top industries
Information Technology, Banking and Finance, Media and Entertainment
Certification focus areas
Information Technology, Project Management, Business Intelligence
Bachelor's degree or higher
100% (Germany: 97%)
Master's degree or higher
67% (Germany: 72%)
Doctorate
17% (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 30 Aug 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 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What they do
AI agents are software systems that can plan steps, use tools, and act on a goal with limited supervision. They are often called autonomous agents or agentic AI. Companies use them to automate support, research, sales outreach, internal operations, and workflow orchestration.
Common builds
- Task assistants that read input, call APIs, and return results
- Multi-step agents that route work across tools and services
- Retrieval-based assistants over company knowledge and documents
- Agent workflows linked to CRM, ticketing, or analytics systems
Core stack
Strong specialists know LLM APIs, prompt design, tool calling, function schemas, memory patterns, and guardrails. They also work with orchestration frameworks such as LangChain, LangGraph, AutoGen, or Semantic Kernel when the project needs structured control. Solid integration skills matter as much as model choice.
When to bring help
Companies usually look for freelance expertise when an idea needs to move from a demo to a reliable system. Common signs are unstable outputs, weak tool use, poor cost control, or unclear safety boundaries. In Frankfurt, this often matters for financial services, logistics, and enterprise teams that need careful process automation.
What good experts deliver
Good professionals do more than wire prompts together. They define agent roles, break tasks into safe steps, design fallback paths, and test for failure modes. They also document behavior clearly so product, security, and operations teams can review how the system acts.
Working setup
AI agents can often be built remotely, but success depends on access to real data, tools, and business rules. For Frankfurt teams, English is usually enough for day-to-day delivery, while on-site sessions help with sensitive workflows and stakeholder alignment. Strong specialists ask precise questions before they build.
Frequently asked questions
Before you brief your next project: the most common questions about AI Agents.
AI agents are used when a system must decide the next step, call a tool, and finish a task with limited hand-holding. Typical use cases include support triage, document processing, research, scheduling, and internal workflow automation. They are a good fit when a simple chatbot is not enough.
A AI agents setup goes beyond conversation and can take actions across tools, data sources, and APIs. A chatbot mainly answers questions, while an agent can plan a sequence, check results, and continue until the task is done. That extra power also means more need for controls and testing.
AI agents projects often start with LangChain or a similar framework, but that is only one part of the stack. Strong experts also know prompt design, API integration, evaluation, observability, and safety guardrails. If the system must work with internal data, retrieval design matters as well.
For a proof of concept, one strong AI agents specialist may be enough. For production work, you usually want someone who has shipped tool-calling workflows, handled failures, and designed clear fallback logic. The right fit should understand both product goals and technical constraints.
Yes, many AI agents projects work well remotely because the core tasks are design, integration, and testing. For teams in Frankfurt, on-site sessions can help when the workflow touches sensitive data, complex approvals, or many stakeholders. Clear access to systems matters more than physical location.
In practice, AI agents and agentic AI are often used to describe the same idea: software that can choose actions instead of only returning text. Some teams use "autonomous agents" for systems that run with less supervision, while "agentic AI" is a broader term. A good freelancer should clarify which behavior you actually need.
A strong AI agents expert can explain the system in simple steps: inputs, tools, decision points, safety checks, and fallback paths. Look for clear examples of evaluation, debugging, and production hardening, not just demo videos. Good work also includes documentation and maintainable prompts or workflows.
Rushed AI agents work often fail in the same places: tool calls break, outputs drift, costs rise, or unsafe actions slip through. Problems also appear when the agent has too much freedom without guardrails. Careful scoping and testing prevent most of that damage.
The average hourly rate of freelancers in Frankfurt, Germany who have used AI Agents in their recent projects is 118 €, which corresponds to a daily rate of about 941 € 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, 67% hold at least a Master's degree, and 17% hold a doctorate.
On average, freelancers in Frankfurt, Germany who have used AI Agents in their recent projects have 15 years of professional experience, with a single engagement typically lasting around 2 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 (15%).
The most common industries among freelancers in Frankfurt, Germany who have used AI Agents in their recent projects are Information Technology (77%), Banking and Finance (54%), and Media and Entertainment (38%).
The most common business areas among freelancers in Frankfurt, Germany who have used AI Agents in their recent projects are Product Development (92%), Project Management (92%), and Information Technology (85%).
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 Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
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Philipp Thomaschewski
FRATCH CEO
