API Gateway Experts in Frankfurt

Participation in the EU-funded MORANE-2 project to validate the Future Railway Mobile Communication System (FRMCS) in real-world use cases: preparation of the requirements specifications for TOBA and the associated test specifications.

Technologies: 5GS (Radio & Core), FRMCS, MCx (MCPTT, MCData, MCVideo), MC Gateway UE, MCx Priority/Security/QoS Management, ETCS, SIP, IMS

• 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.

• Responsible for the end-to-end application and integration architecture for the S-Bahn Hamburg maintenance digitalisation program. A highlight is the introduction of robots and permanently installed camera gates to automate vehicle inspections, allowing AI image algorithms to assess the condition of trains during operation.
• Deutsche Bahn has one of the largest SAP PM implementations in the world, which is a central component of this digitalisation.

• Agile coach and scrum master in property insurance/underwriting for Allianz Technology
• Team 1: Kanban/Scrumban team in DevOps mode – new features, distributed monolith to microservices, reduction of technical debt & refactoring, implementation of CI/CD, expansion of automated testing
• Team 2: SAFe team – greenfield service for global software and German adaptation, AI integration (Cythora)
• Scrum trainings, scrum manuals in Confluence, all ceremonies, establishment of an experimental just culture, team replacement and scaling from 7 to 20
• Requirements engineering, prioritization via business value for product owners, risk identification
• Project budget management, JIRA monitoring and automation, steering committee support, test strategy
• SAFe integration, PI planning, flight levels and road mapping

• Presentation introducing generic A.I. and Large Language Models
• Explanation of legal frameworks (EU AI Act, US CLOUD Act, DSGVO)
• Systematic review of AI tools along the SDLC and holistic systems
• Comparison of on-prem LLMs vs. cloud-based solutions, as well as change management and works council considerations
• Moderation of the discussion and definition of next steps for introducing AI development tools

• Designed and implemented the agent-based AI architecture for a company-wide platform to securely deploy LLM-based agents
• Designed and implemented end-to-end RAG pipelines from multiple sources: document preprocessing, chunking strategies for different document types, embeddings, retrieval with re-ranking, and robust prompt orchestration
• Developed a modular context engineering framework with skill architecture, context isolation, and dynamic resource management; human-in-the-loop control for enterprise tool integrations
• Built the CI/CD pipeline, testing strategy, tracing on the software side as well as automated LLM and agent evaluations, red team testing and tracing, and handed over to a reproducible production environment (ISO27001 and SOC2 compliant)

• Engineered production-ready Azure environments using Terraform, ensuring consistent infrastructure parity across VNets and Resource Groups
• Implemented Microsoft Fabric tenant and workspace architecture for multi-stage Medallion data processing pipelines
• Designed secure data pathways using Managed Private Endpoints for isolated Azure Storage access
• Managed Service Principals and authentication tokens for secure REST API integrations

• Devised a new Domain-Driven Design architecture for a core system: reverse-engineered a central component, refactored the data-access layer to minimise database round-trips (improving scalability) and migrated processing to async.
• Decomposed the platform into independent .NET Core microservices (database-per-service) with RabbitMQ pub/sub using the Outbox Pattern + Saga choreography, behind an Ocelot API Gateway (JWT, rate limiting, CORS, health checks).
• Delivered on .NET Core / Angular / SQL Server / EF Core with Docker and Azure DevOps CI/CD; implemented health checks and CORS; contributes technical designs for stories in agile Scrum.
• Sole ADR owner; mentored 3 engineers and presented architecture decisions directly to the Director of Corporate IT.