luisdelatorre.de

Luis Fernando De La Torre Delgado

Cloud & AI Solutions Architect, Hamburg

I design and build agentic AI systems, on AWS or where the data has to stay in Europe, and I teach engineering teams to work with them.

Experience
18 years in software engineering and architecture
Domains
Circular economy, FinTech, gaming, EU research projects
Certified
AWS Certified AI Practitioner
Luis Fernando De La Torre Delgado, studio portrait

Architecture and delivery

Agentic AI systems from architecture through to production. I have built several of them, on AWS and on EU sovereign infrastructure. That means I can deliver on a hyperscaler, and I can deliver when the data has to stay under European control.

AWS Lambda, Bedrock, serverless production systems
EU sovereign infrastructure Model, data and hosting under European control
Agentic
LangGraph, MCP, evaluation and guardrails
Infra
Terraform
Code
TypeScript, Effect-TS, Python

Agentic Enablement

A two day workshop for engineering teams, followed by optional mentoring.

Day 1
The four pillars of agentic engineering: what the agent is asked to do, what it knows while doing it, how its work is verified, and what it is allowed to touch. Then a guided lab builds an application from an empty repository.
Day 2
The same workflow applied to real issues from your team's own codebase.
Ongoing mentoring
Optional weekly sessions that establish the workflow in everyday team practice.
Every cycle produces
A specification, a decision log, a sandboxed execution setup, an evidence matrix and a release-readiness package.
Format
Two days, onsite or remote
Tools
Claude Code, Codex, OpenCode
Method
Spec driven development, hooks, sandboxing, evaluation

German companies with fewer than 50 employees can have up to 100 percent of the training cost subsidised through the Qualifizierungschancengesetz.

Ask about a workshop date

AI-assisted review of railway construction plans

Measured
97.5% exact on 80 gold-standard requirements
In the same evaluation: 100% of planted gaps found, 0 invented findings, 0 successful prompt injections.

An engineering office that reviews railway construction submissions wanted to know whether an AI agent could check real plan sets against real regulations without inventing findings. In five weeks I built a browser-based system that checks completeness, text requirements and the drawings themselves. The drawings were the focus: that is the part a text-only check cannot reach. Every finding carries its regulation reference, document, page and quote, or it is not reported.

Client
Engineering office, rail infrastructure, Germany
Scope
Fixed price, five weeks, built solo
Stack
Bedrock, Lambda, DynamoDB, React, Terraform, eu-central-1

EU-hosted AI tutor for public-sector training

Status
MVP in progress
Not yet in production.

A municipal training provider wants to bring AI into its courses without giving up control over where its data goes. We are building an MVP of a learning platform on one non-negotiable: model, data and hosting stay in Europe. The architecture is deliberately small. Every AI step sits behind a human decision, and the model runs behind an abstraction layer so it can be swapped without touching the rest of the system. Where a common pattern is not needed yet, we leave it out and document the trigger that would bring it back. Sensitive data is kept away from the model by design, not by policy. The goal is an MVP the client can run, extend and audit from day one, not a demo that has to be rebuilt before production.

Client
Municipal training provider, through a public consulting programme
Stack
Mistral Large 3 pinned, TypeScript, Effect, PostgreSQL, GPU capacity in Germany

Agentic engineering enablement for an insurance broker pool

Scope
Two two-day workshops, followed by five weeks of mentoring with three teams

Two two-day workshops with the engineering organisation of a German insurance broker pool, then five weeks of mentoring with three of its teams. The workshops run the four pillars and a guided lab that builds an application from an empty repository, with architecture guidelines and hooks that enforce them, then a second day on real issues from the teams' own code. The mentoring is the part that decides whether any of it survives contact with a backlog: the same cycle, run by the teams themselves, on their own work, week after week.

Client
Insurance broker pool, Germany
Tools
Claude Code, Codex, Playwright, Bun, Effect
Also run for
An online fashion retailer, Germany, August 2026: three applications built from scratch on day one, participants' own issues shipped on day two

Let us talk about your project or your team.

I work remotely from Hamburg and travel for occasional onsite days across Europe.

Languages
German, English, Spanish
Location
Hamburg, Germany
Mode
Remote, occasional onsite across Europe
Booking
cal.com/luis-fernando-de-la-torre

Book a call