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Quality Engineer · AI Architect · System Thinker

Here's to the ones
who automate
the impossible.

Michael Boiman

Michael Boiman

Quality Engineer · AI Architect

Frankfurt am Main

Freelance Quality Engineer & AI Architect. Available for QE and test-automation projects, AI architecture, and AI workshops.

20+ years in Quality Engineering
40+ automations in production

40+

Skills

one orchestration hub

20+

Repos orchestrated

across 7 project boards

Live

AI agent

this CV answers for itself

Everything AI needs today — reliability, measurability, self-correction — I have been building into systems for two decades, with and without AI. Quality engineering and AI architecture run in parallel for me — each makes the other better.

AI & DevOps

AI Context Orchestrator — Multi-Repo Development Platform

Challenge

Enterprise development across 20+ repos, multiple customers and diverse tools required constant context switching and manual coordination.

Solution

Central control system with ecosystem.yaml as single source of truth, 40+ skills and hook-based permission system.

AI-assisted workflows from incident response to meeting documentation — orchestrated through one central hub.

40+ Skills
Enterprise Integration

E-Invoicing Automation Platform

Production E-Invoicing Pipeline (Peppol/EN 16931)

Core Features:
Peppol Network Integration: Connection to European e-invoicing network via Storecove Access Point
Multi-Format Support: ZUGFeRD, Factur-X, XRechnung, UBL 2.1, CII (EN 16931 compliant)
ERP Integration: Automatic transfer to SAP ByDesign with validation and error handling
Hexagonal Architecture: Domain-driven design with Ports & Adapters for maximum testability
Dual-Channel Inbound: Storecove Webhook (Push) + Email Inbox (Pull) for redundant processing

Impact: Production system — Peppol connectivity per EN 16931, automated inbound and outbound invoice processing across the Storecove route into SAP ByDesign.

Training & Workshops

Developer Workshop: AI-Agent Development & Integration

Target Audience: Developers, Technical Leads, DevOps Engineers

Workshop Content:
Hands-on AI Agent Development: Live coding with Claude, Gemini, GPT-4o
Next-Gen Protocols: MCP & A2A implementation for enterprise integration
Browser Automation: Playwright-MCP for automated test generation
IDE Integration: AI assistance workflows — Claude Code as primary stack, GitHub Copilot & VS Code as tool comparison
Multi-Agent Orchestration: JSON-RPC, secure agent communication
Practical Demos: Jira integration, Elasticsearch queries, GitHub workflows

Deliverables: Complete source code, slides, hands-on exercises, production-ready templates

Consulting & Strategy

Enterprise AI Consulting: From Strategy to Implementation

Challenge

Organizations recognize AI potential but lack a structured path from vision to measurable implementation.

Solution

End-to-end consulting with strategy development, ROI assessment, executive workshops and implementation support.

Measurable AI roadmaps with concrete business cases — from strategy directly to productive solutions.

E2E vision to production
Quality Engineering

Quality Dashboard - Real-time Overview

Challenge

Go/No-Go decisions required hours of manual data gathering across 10 test tools, 5 environments and multiple data sources.

Solution

End-to-end pipeline with real-time dashboard, multi-source integration and automatic PDF report generation.

Data-driven release decisions in real time across 10 test tools and 5 environments, with automated PDF reports.

10 test tools unified

When you have 10 tools and no overview, you have zero tools.

A million combinations no human can test. But a machine that never sleeps, can.

The best test is the one a developer never had to write.

Automation without measurability is just faster guessing.

Professional Experience

Guest Lecture: AI-Assisted Software Development in Practice

04/2026

TU Darmstadt — Information Systems Group · Lab course “AI Startup: From Idea to Execution”

Invited guest speaker in a block lab course for Bachelor's students in Computer Science (Dept. 20). Shared how agentic coding and AI prototyping work in real projects — directly applicable to the students' subsequent team work on their own startup ideas.

Topics
• From prompt to prototype: AI toolchains that get an MVP done in hours, not weeks
• Agentic coding in practice — where it scales, where the friction sits, where tools break down
• Live demos from my own skill ecosystem, on demand in response to the group's questions
• Lessons from production AI projects rather than slide theory

Format: moderated impulse talk with interactive live demonstrations. Audience: ~25 students with mixed prior knowledge.

Workshop: Development with Generative Language Models

06/2025

Developer Workshop - Agent-based Software Development

Developer Workshop: Comprehensive workshop on modern AI agent development with practical demos and live coding

Workshop Content
• Development with LLMs (Claude, Gemini, GPT-4o) and token optimization — used across projects
• Model Context Protocol (MCP) & Agent-to-Agent (A2A) protocol implementation
• Google Agent Development Kit (ADK) for multi-agent systems and tool integration
• Agent orchestration with JSON-RPC and multi-agent systems
• Browser automation with Playwright-MCP for automated test generation
• Live demos: Jira integration, Elasticsearch queries, GitHub workflows
• Prompt engineering & rule-based agent control (CLAUDE.md, instructions)
• TDD workflows with AI assistance and automated PR creation
• Task Master AI agent for project management and code scaffolding

Technologies & Tools
• Anthropic Claude, Google Gemini, OpenAI GPT-4o
• Google Agent Development Kit (ADK), Model Context Protocol (MCP), Agent-to-Agent Protocol (A2A)
• Claude Code as primary stack; GitHub Copilot & VS Code AI extensions covered as tool comparison
• Playwright, browser automation, web scraping
• JSON-RPC, REST APIs, multi-agent communication

Complete workshop with slides, live demos, and practical exercises for modern AI-assisted development workflows.

LLM Infrastructure Architect & Automation Engineer

06/2025 – present

BKS - AI Research & Development

Development of LLM-orchestrated Enterprise Development Ecosystem: Fully integrated system for knowledge management, project automation, and development workflows with Claude, Gemini, and OpenAI GPT.

Key Responsibilities
Open Source MCP Server Portfolio: Development and publication of 3+ MCP servers on GitHub (bks-wiki-mcp, hubspot-mcp-bks, bks-codex) with uvx distribution, Claude Desktop integration, and multi-format support (Markdown, JSON, YAML)
Multi-Agent Orchestration System: Implementation of production-ready A2A system with Orchestrator Agent (routing hub) and Knowledge Agent for inter-agent communication, capability-based Agent Cards, and JSON-RPC 2.0
Git Wiki Transformation: Migration of Confluence knowledge base to structured Git-based wiki with hierarchical organization and multi-repository architecture (submodules for customer projects)
MCP Navigation Server: Development of Model Context Protocol server (Python) with intelligent hierarchy navigation, automatic content discovery, and SharePoint integration
Google ADK Integration: Implementation of Google Agent Development Kit for multi-agent systems and advanced tool integration
GitHub Project Automation: LLM-driven issue management with 7-mandatory-field system, automatic categorization, smart repository mapping, and review queue management
Development Workflow Automation: GitHub Actions workflows for fully automatic issue-to-PR transformation (assignment → feature branch → implementation → code review → PR)
Self-Documenting System: LLM automatically writes project status, meeting protocols, and issue updates back to Git wiki; closed loop of wiki reading → work execution → results documentation → Git commit with structured logging
Time Tracking Integration: Commit-based work time analysis with automatic Clockify synchronization, intelligent project assignment, and BKS formatting
Claude Code Plugin Ecosystem: Development of 40+ skills for enterprise workflows — log analysis, deployment verification, incident handling, email management, meeting transcription, PDF/certificate generation, SharePoint integration
Context Orchestrator: Central multi-repo control system with ecosystem.yaml as single source of truth for 20+ repositories, automatic cross-repo navigation and structured work tracking with archiving
Hook-based Permission System: Smart Guard with project-specific security rules for Git operations — branch protection, secret detection and deployment gates
Production Operations E-Invoicing: Ongoing management of an e-invoicing platform for a leading online job platform (under NDA) — automated incident management, log analysis, weekly reporting and go-live tracking
Self-Operated Infrastructure: hub and services run on own hardware (launchd services, device fleet over Tailscale) with a 3-2-1 backup strategy (restic/rclone to NAS).

Tools & Technologies
• LLM Orchestration: Claude (primary), Google Gemini, OpenAI GPT, Model Context Protocol (MCP), Google Agent Development Kit (ADK)
• AI Development Platform: Claude Code, Plugin Architecture (Skills, Hooks, Commands, Agents), YAML/Markdown Configuration
• Multi-Agent: A2A Protocol, Orchestrator/Knowledge Agents, Agent Cards, JSON-RPC 2.0, SSE Streaming
• Backend: Python 3.13, FastAPI, uvx Distribution, Git Submodules
• Automation: GitHub Actions, GitHub GraphQL API, gh CLI
• Integration: SharePoint API, Clockify API, Elasticsearch, Natural Language Processing
• Development: Bash Scripting, jq, Docker, Multi-Agent Systems; orchestrated repos span Python, TypeScript, Rust and Go

Quality Engineering

09/2025 – present

TÜV Süd

Quality Engineering for an enterprise platform for AI-powered document processing in medical device certification (MDR/IVDR) with AI chat integration and data pipeline automation.

Key Responsibilities
BDD API Test Framework: Development of comprehensive test framework with Python/Behave, self-healing authentication, HTML report generator with embedded API responses
E2E Test Automation: Playwright E2E test suite for complete user journey (Setup -> Upload -> Transformation -> Download) with 500 error handling and route mocking
Performance & Monitoring: Development of Azure Monitor Workbooks (QA Live Testing Companion, Error Investigation Assistant) with KQL for end-to-end monitoring
Bug Analysis & Quality Intelligence: Implementation of comprehensive bug tracking system with WIQL queries, automated dashboards, and executive PDF reporting
Pipeline Integration: Test automation in Azure DevOps CI/CD pipelines with HTML report upload to Azure Test Results
AI-Powered Automation: Development of automation skills for workflow optimization, bug analysis, and incident response with measurable time savings

Tools & Technologies
• Testing: Behave, Playwright, TypeScript, Python, pytest, Page Object Model, Fixtures
• Monitoring: Azure Monitor Workbooks, KQL, Application Insights, Log Analytics
• Backend: FastAPI, Python, Pydantic, SQLModel, Azure Functions, Azure Service Bus
• Frontend: React, TypeScript, Vite, TanStack Router
• AI Integration: Azure OpenAI (GPT-4o), LangChain, Azure AI Search, Embeddings
• DevOps: Azure DevOps Pipelines, Git, Docker, Azure Blob Storage, Poetry

AI-driven Automated QA Environment for Energy Infrastructure

07/2024 – 01/2025

AkkuSwap Startup

QA Leadership for EU-wide Battery Swap Infrastructure: AI-driven simulation tool for battery swap station network with energy infrastructure integration

Key Responsibilities
• QA concept, design and implementation for AI-driven simulation of EU-wide infrastructure
• QA framework development for inhouse AI server infrastructure
• Proof-of-concept for automated testing of AI-driven simulations

Energy Sector Connection
50 Hertz Participation: 50 Hertz (Elia Group subsidiary) participated in research project eHaul, the predecessor of AkkuSwap
• Direct energy sector experience with critical infrastructure quality requirements
• Context of critical energy infrastructure (transmission-grid environment)

Technical Stack
• Infrastructure: Linux, Docker, Azure OpenAI
• Automation: pytest, AI code generation integration patterns
• Monitoring: Grafana, Azure Monitoring
• Energy Systems: Battery swap infrastructure, grid integration simulation

Key Achievements
• Established QA methodology for AI-driven infrastructure simulation
• Created testing framework for energy sector critical systems
• Validated proof-of-concept with measurable reliability improvements

Earlier Positions

Presentation: Efficient Documentation through Automation — Enterprise Presentation - AI-powered Documentation Workflows
04/2025
Platform Quality Architect (CI/CD, Monitoring, Automation) — DVAG
08/2021 – 05/2025
Technical Lead & AI Automation Architect — BKS
01/2024 – 04/2025
AI Engineering Lead & ML Solutions Architect — BKS on behalf of Ryze
04/2023 - 04/2024
Applications of AI in Business Context — AI Workshop for Business Integration
2023
DevOps Quality Lead & Dashboard Architect — DB Vertrieb
01/2017 - 05/2021
Performance Engineering Lead & Test Architect — DB Systel
09/2015 - 01/2017
Senior iOS Developer & Mobile Architect — Telekom
04/2015 - 09/2015
Quality Assurance Lead & Test Automation Architect — Siemens
05/2009 - 03/2015
Performance Test Engineer & Load Testing Specialist — ING-DIBA
03/2009 - 05/2009
Performance Test Engineer & Quality Consultant — British Telecom, Mobiliar, DB-Systel, Sparkassen Informatik, Loyalty Partner, Telekom, Itelium, Deutsche Post, Postbank
01/2006 - 12/2008

Education

Diploma in Computer Science (UAS)

Cologne University of Applied Sciences, Gummersbach

2000 – 2005

ISTQB Certified Tester

2005

Certified Dynatrace Diagnostics Basic Training

2007

Languages

German Native
English Professional

Skills

Quality Engineering · Playwright · Cucumber/Gauge · Python · Claude Code (Skills, Hooks, MCP) · LLMs (Claude, Gemini, GPT) · Agent Orchestration (MCP & A2A) · Google ADK · LangChain · Peppol/E-Invoicing (EN 16931) · CI/CD · Kubernetes · Azure Functions · Grafana · Elasticsearch · REST APIs · Docker · JMeter · Gatling