Backend-focused full-stack engineer building reliable domain systems, APIs, and data workflows.

I work across PHP/Symfony, TypeScript/Node.js, Java/Kotlin, and Python. My focus is evolving business rules safely, designing secure integrations, and delivering changes with tests, static analysis, migrations, rollback plans, and production-minded verification.

Building personal software since 2013. My public work combines current inspectable code, sanitized engineering case studies, and reusable AI-assisted engineering practices.

I use AI-assisted tools within a human-owned engineering process: explicit scope, repository safeguards, tests, security checks, review, and evidence-backed acceptance.

• Equipment Service Desk: A synthetic PHP/Symfony backend demonstrating policy-based triage, authorized workflows, conflict-safe updates, transactional persistence, and asynchronous reports.
• Engineering portfolio — Architecture, trade-offs, testing, security, and delivery lessons from domain systems, modular platforms, and local-first data.
• AI-assisted engineering playbook — Reusable templates, repository safeguards, tested utilities, and a complete fictional delivery example.
• Local-first reconciliation — A current Python and SQLite project using provenance, dry-run planning, guarded synchronization, and conservative failure handling.

• Domain backends, evolving business rules, APIs, and asynchronous processing.
• Data modelling, persistence, ETL, reporting, reconciliation, and migrations.
• Authentication, authorization, secure integrations, and failure-closed behavior.
• Testing, static analysis, CI/CD, rollback, smoke testing, and production diagnosis.

I am most at home in backend work where correctness spans code, configuration, persisted state, and delivery. That includes PHP, Symfony, Doctrine, and PostgreSQL as a primary stack, with broader work across TypeScript services, JVM systems, Python tooling, relational and document databases, containers, and cloud delivery.

I prefer explicit system boundaries, small reviewable changes, and evidence that matches the claim being made. In practice, that means tracing a rule across its consumers, testing failure paths, separating configuration from authority, and treating rollout, observability, and recovery as part of the implementation.

The linked case studies use sanitized architecture, synthetic examples, and original diagrams. They describe real engineering decisions without publishing proprietary source, operational data, or identifying organization details.

Open to remote roles and employer-supported relocation.

Working languages: Dutch, English, French, and Spanish.

Recruiter contact: email me