I work on complex systems
where architecture actually matters.
I'm a software consultant focused on building and evolving complex systems — from distributed architectures to AI-driven platforms.
Most of my work starts where things stop being simple: scaling issues, unclear system design, or machine learning models that need to work in production, not just in theory. I work across the full stack, but my focus is on making systems reliable, maintainable, and aligned with real-world constraints.
I've worked on financial systems, medical AI research, and enterprise software — including machine learning models for medical imaging and automation systems for accounting workflows.
I want to help teams and companies build software that can grow and adapt over time, without falling apart as complexity increases.
If that sounds like a challenge, we should talk.
const ChG4bbo = {
focus: "Complex Systems & AI",
approach: "Architecture first",
mindset: "Complexity is a challenge",
building: [
"Full stack App",
"AI systems",
"Scalable platforms",
],
};
export default ChG4bbo; Tools & Technologies
The technologies I use most, built up through years of working on real systems.
Languages
Backend & Frameworks
Frontend
AI / ML
Cloud & DevOps
Data
Professional Journey
Key roles that shaped how I think about systems and software.
Software & AI Solutions Architect
Independent
- Design system architectures for clients in finance, healthcare, and enterprise software
- Build and deploy ML pipelines that run in production, not just notebooks
- Lead technical decision-making on distributed systems, data models, and integration strategies
Full-Stack Developer
Tecnos Group SRL
- Designed and maintained accounting systems handling real-world financial workflows
- Built ML-based classification pipelines for bank transaction reconciliation, integrated into production
- Worked on system reliability, data integrity, and performance under daily operational load
AI Researcher
Aigon SRL
- Developed deep learning models for medical imaging: Alzheimer detection from MRI, tumor classification
- Built multi-modal pipelines combining imaging data with genomic features
- Co-authored a patent on diagnostic methodology with the research group
Approach & Principles
The engineering principles behind how I design and build systems.
System Design Over Features
I focus on how components interact, fail, and evolve — not just what they do today. Features change; architecture decisions compound.
Trade-offs and Constraints
There are no perfect solutions. I make trade-offs explicit — between cost, complexity, performance, and team capacity — and choose what fits the real context.
Production-First Mindset
A system that works in staging but breaks under real load is not done. I design for production conditions from day one: observability, error handling, data integrity.
Long-Term Maintainability
Code lives longer than the team that wrote it. I structure systems so they remain understandable and changeable without requiring the original author.