Hiring: lead developer and architect
An engineer trained in AI and robotics, with several years in large groups. I designed, shipped and operated an entire information system on my own.
Résumé available on request
Professional background
Defence, energy, space, aeronautics, AI research.
Organizations listed as experience references. Logos remain the property of their owners.
Profile
What you need to know in one minute.
Engineering school degree in AI and robotics, then several years of development in large groups.
Understand the business before coding, design simple and safe, prove every delivery.
An end-to-end view and a method to bring in AI agents without losing control of the code.
Skills
Skills used together, on applications running in production.
Stack
Know-how: Idempotency, concurrency locks, workers, scheduled jobs, workflows and state machines.
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Know-how: PDF generation, electronic signature, field photo capture, technical SEO.
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Know-how: HttpOnly sessions and CSRF protection, AES-256-GCM encryption, rate limiting, server hardening.
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Know-how: Reproducible deployments, rollback by tag, monitoring, alerting and deduplicated pull-mode backups.
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Know-how: Online payment, ERP, electronic invoicing, calendars, transactional emails, and point-of-sale hardware.
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Know-how: Engineering degree in AI and robotics: ML, deep learning, reinforcement learning, NLP, explainability.
Artificial intelligence
A skill in its own right, which I practise and can spread across a team.
Engineer first. AI executes; I design, decide, review and prove.
I do not delegate my understanding: every change is reviewed, and I keep the final say.
Versioned specs split into deliverables with acceptance criteria; one instruction contract per repository.
Evidence: A 28-deliverable roadmap drove the SSO rollout across 9 applications.
A plan approved before any code, specialized sub-agents, worktrees to parallelize without conflict.
Evidence: A fresh session executes another one's plan: no confirmation bias.
Deterministic hooks, restricted permissions, no secret handed to AI, explicit human escalation.
Evidence: Guardrails are technical, not just instructions.
Tests written first, then multi-agent testing in a real browser; every verdict is re-measured.
Evidence: 5 campaigns, over 800 cases, up to 11 agents in parallel.
Every change reviewed, architecture and security calls made by me. No code I do not understand gets merged.
Evidence: I remain accountable for what goes to production.
Reusable skills, a wiki updated in the same patch, memory shared between agents.
Evidence: Active watch: spec-driven development, MCP, Claude Code, Codex.
Shared rules rather than individual habits.
An instruction contract per repository, versioned specs and a common definition of done.
Reusable workflows (feature, acceptance testing, diagnostics) versioned with the code.
Hooks, permissions and mandatory reviews: a technical frame, not just a declared one.
Helping developers move from improvised prompting to a measurable engineering practice.
Work
The technologies, the responsibilities and the problems solved.
Replacing a legacy tool with an in-house platform, built from scratch.
An internal web application for cataloguing and search, built from scratch by a team of seven whose architecture and code review I own.
13 interconnected apps: sales, workshop, rentals, invoicing and e-commerce
A complete information system for an SME: central API, e-commerce, ERP and point of sale, SSO and 6 business apps.
E-commerce API, storefront and back-office, with an ERP-driven catalogue
A 3-app headless e-commerce platform: ERP-driven catalogue, Mollie payments, legal invoicing and returns handling.
One identity, a second factor and central revocation across 9 applications
Self-hosted OIDC single sign-on for 9 applications: passkey or TOTP MFA, server-side tokens and migration with no lost access.
Dolibarr 22 with 8 custom modules, a connected POS and e-invoicing
Dolibarr 22 ERP with 8 custom modules: hardware-connected point of sale, offline inventory and a 4× faster product list.
One backend for the workshop, rentals, sales, invoicing and bank reconciliation
Central Node.js API: ~250 endpoints, 44 data models, quotes signed online, idempotent invoicing and server-side OIDC SSO.
Engineer first: AI executes; I design, decide, review and prove.
Versioned specs, skills and multi-agent browser testing: an AI pipeline under engineering control, with over 800 test cases run.
What I'm looking for
Roles where architecture, quality and agentic AI carry real weight.
Own the technical quality of a product and support a development team.
Design and evolve complete, secure and maintainable systems.
Structure how a team uses AI agents: methods, tools and safeguards.
Other needs
The same background, for another need.
Tell me about the role and the technical stakes. CV on request.
