I have spent 16+ years building software, designing architectures, modernizing complex systems and leading engineering organizations — while staying close to the technical problems that actually constrain delivery.

My approach is simple:

Understand the problem. Find the constraint. Build the capability needed to overcome it.

Over the years, that has meant everything from modernizing critical Java platforms and building engineering standards to scaling Internal Developer Platforms across ~50 squads and leading engineering organizations of up to ~220 people.

Today, I'm particularly interested in how Artificial Intelligence can become the next capability layer for software engineering.

Designing systems that remain understandable, evolvable and resilient as they grow.

Building platforms, golden paths and engineering capabilities that reduce cognitive load and make the right way the easiest way.

Exploring how LLMs, RAG, agents and AI-assisted workflows can improve software delivery, architecture and developer productivity.

Building technical capabilities, creating context and enabling engineering organizations to solve harder problems independently.

• Led engineering organizations of up to ~220 engineers.
• Built and scaled an Internal Developer Platform across ~50 squads.
• Reduced production-ready microservice provisioning from ~2 weeks to <1 hour.
• Defined GitHub Copilot adoption for ~500 internal developers.
• Improved conversational-system conversion from ~50% to ~80%.
• Modernized 16 instances of a critical Java platform with no customer impact.
• Reduced certificate-expiration incidents from ~1 per month to zero.

I'm currently deepening my work in Applied AI through hands-on projects and a Master in AI Development.

Areas I'm exploring:

• AI Engineering
• LLM applications
• RAG architectures
• AI Agents
• Model Context Protocol (MCP)
• LLM evaluation
• AI-assisted Software Architecture
• AI-powered SDLC
• Developer Experience
• Engineering Productivity
• Legacy modernization with AI

experience: 16+ years

focus:
  - Software Architecture
  - Platform Engineering
  - Applied AI
  - Engineering Leadership

background:
  - Software Engineer
  - Software Architect
  - Engineering Manager
  - Engineering Platform Tribe Lead

industries:
  - Banking
  - Enterprise Software
  - Consulting

Java
JavaScript / TypeScript
Python

Distributed Systems
Microservices
Event-Driven Architecture
APIs
Hexagonal Architecture
CI/CD
Observability
SRE
Developer Experience

GitHub
GitHub Actions
Jenkins
Docker
Kubernetes / OpenShift
Cloud Platforms

LLMs
RAG
AI Agents
Prompt Engineering
MCP
LLM Evaluation

Python and modern AI technologies are part of my current hands-on learning and project work; my deepest professional experience remains in software engineering, architecture and engineering platforms.

This section will evolve as I publish current AI and software-engineering work.

I'm particularly interested in projects that combine:

• AI agents with real engineering workflows
• RAG and knowledge systems
• AI-assisted architecture decisions
• Legacy modernization
• Engineering productivity
• Measurable evaluation of AI systems

• Technology is a means, not the objective.
• Understand the constraint before optimizing the system.
• Build capabilities instead of relying on heroes.
• Developers deserve great tools.
• Make the right path the easiest path.
• Measure outcomes, not activity.
• Simplicity scales better than unnecessary complexity.
• Leadership requires technical credibility.
• Context scales better than control.
• AI should amplify engineers, not replace them.

I'm currently completing a Master in AI Development at The Big School, with a focus on:

• Generative AI
• LLM applications
• RAG
• AI agents
• MCP
• LLM evaluation
• AI-enhanced software development
• Production-grade AI systems

When I'm not building or learning, you'll probably find me:

• 🎨 Painting Warhammer miniatures
• ⚔️ Exploring Warhammer 40K lore
• 🏃 Training
• ☕ Experimenting with coffee
• 🌱 Learning something new

Building capabilities to overcome constraints.