AI Agents Experts in Frankfurt

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

• Functional requirements management for DIVID, the Umweltbundesamt platform for administering the single-use plastics fund. Focus: entitled parties, sub-entitled parties, and benefit reports.
• Consolidation and analysis of specifications, Jira, Confluence, functional concepts, and UX designs. Independent structuring and delimitation of requirements, as well as identification of contradictions, gaps, and dependencies.
• Creation and quality assurance of implementable user stories with clear, testable acceptance criteria. Preparation of decision alternatives and coordination with business, development, UX, and QA through team refinement.
• Conducting manual and technically assisted accessibility tests. Coordinating findings with QA and the Product Owner for further planning and implementation.
• Result: more consistent requirements, clearly defined processes and stories, and transparent open decisions. Separation of assumptions from confirmed requirements; better basis for implementation, refinements, and QA test cases.

Tools used: Jira, Confluence

• 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.

• Designed and implemented modular AI assistants for sales and business processes within 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 servers, 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, and mentoring within 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

• 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

• 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.
• Building an AI-native enterprise platform that structures organizational data, workflows and responsibilities for both people and AI agents.
• Models accountability through RACI, allowing human and AI participants to take different operational roles, including Responsible, Accountable, Consulted and Informed. AI agents can also take controlled approval roles where the organization assigns that responsibility.
• Extended the organizational and operational-risk themes from my Executive MBA thesis into software, making roles, processes and controls explicit and machine-readable.
• Structures enterprise context so LLM interactions use more relevant information instead of repeatedly processing large amounts of unstructured content.

Independently built a data platform with cross-system process monitoring.

• Designed the Bronze/Silver/Gold architecture and Python-based pipelines for diverse operational sources.
• Cleaned, harmonized, and validated data; processed and stored it in Parquet format.
• Tracked data history and built business-focused fact and dimension models for traceable reporting.
• Automated data delivery with Python and Power Automate (desktop and cloud); used SharePoint for archiving and data access.
• Developed the Power BI solution from data preparation through to visualizing process statuses, work progress, and deviations.

Technologies: Python, SQL, Parquet, Power BI, Power Query, Power Automate, SharePoint, Copilot

• Responsible for the concept, planning, and delivery of product development for GetMyInvoices 2.0 and its subcomponent InvoiceRails
• Independently handled all aspects of the project, including concept development, writing ticket specifications, and coordinating developers
• Created, managed, and prioritized tickets to ensure all tasks were completed on time and to a high standard
• Conducted and/or coordinated tests and ensured the proper implementation of developed features and functionality
• Worked closely with developers to clarify technical requirements and ensure implementations met specifications
• Regularly reported on project progress and documented key decisions, changes, and risks
• Took the lead on all topics related to e-invoicing and Peppol, especially regarding the InvoiceRails component
• Provided internal guidance and shared knowledge about e-invoicing and Peppol with other teams and departments
• Tracked market trends and new developments in e-invoicing and Peppol to continuously adapt the product strategy
• Ensured the products’ long-term scalability and adaptability to future technological and legal changes in e-invoicing

• 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

• 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.

• Steer innovation projects for AI-based systems, focusing on plant detection technology for agricultural applications.
• Champion digital transformation initiatives within software departments, advocating for Agile methodologies and Scrum-based workflows.
• Analyse and optimise team infrastructure, fostering a culture of continuous improvement and strategic development.
• Pioneered integration of AI technology in agricultural equipment, significantly advancing precision farming techniques.
• Designed a cloud-based dashboard platform, facilitating real-time data access and decision-making for field management.
• Developed camera-based GPS systems for tractors, enhancing field analysis capabilities.
• Created and implemented AI interfaces for pre-processing image data, ensuring seamless statistics delivery to the cloud via LTE.
• Innovated cloud-based dashboard platforms, introducing cutting-edge technology concepts and coordinating cross-functional teams to execute project visions.

• 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.

• 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.

• 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