Founding AI Engineer

Over deze functie

Before you read further HelloPrint is on a mission to become the world's leading infrastructure for customizable printed products. From our offices in Rotterdam and Valencia, 120+ professionals from 20+ nationalities are building an AI-first company that scales output faster than headcount. We're at EUR 100M revenue and aiming to disrupt a trillion-dollar industry. Every hire we make needs to help get us there.

Commercial instinct first, engineering second. You think about what something is worth before you think about how to build it.

Full-time in Rotterdam. Five days a week, in the building where the transformation is happening. This is not negotiable.

Always on mentality. This is not a 40-hour job; it’s a deliberate choice into something big that requires “what it takes”

You have been building since before it was a career. Side projects, tools, systems nobody asked for. The obsession came first.

You ship continuously. Not when it is ready. Not when it is perfect. When it moves a metric.

With our new approach, we ship in a week what used to take a year, and we are looking for someone who raises that bar further. HelloPrint is not exploring, we are completely transforming into a fully AI-first organisation. The entire platform is being rebuilt from the ground up: new frontend, new pricing engine, new content engine, new product engine; Everything ready for an agentic future. No one on the team writes code manually for what these systems handle.

Why this role exists: We can find excellent engineers, but what we’re looking for are people for whom building and commercial thinking are not two separate things. As a founding AI engineer, you will work directly alongside our founding team, including Hans (CEO) and Michael (CIO / Chief AI Officer). We have no hierarchy, no management layers and no decision trees. Everyone at HelloPrint builds, the founding team included. The expectation for this role is identical to every other builder: see the highest-impact problem, own it, ship it, measure it, move to the next one.

This role is not for people who got into AI because it became important. It is for people who have been building since before anyone called it a career. The kind of person who coded as a teenager, shipped their first thing before anyone asked, and has never really stopped. Who finds it genuinely difficult to explain why they build: it is just what they do. Who would rather spend a Sunday solving a hard systems problem than almost anything else. If you have to think about whether that description fits you, it probably does not.

This role will resonate with a specific kind of person. You will recognise yourself in one of these profiles:

You are a technical co-founder or CTO 2 to 4 years into a startup. Your systems work. Your customers are real. But growth has plateaued and the funding environment is harder than expected. You are spending 30 to 40% of your time on things that are not building: investor relations, cap table management, pivot conversations. Your work reaches thousands of users. HelloPrint reaches 600,000.

Or you are a senior AI builder at a fast-growth scale-up. Technically exceptional. Commercially disconnected. Here every build decision is also a business decision, immediately visible in revenue.

Or you are building independently: open-source tools, AI SaaS, consulting. Commercially restless. HelloPrint offers better equity, better compensation, and 600,000 customers to build on immediately.

What you will build: There is no pre-written roadmap. Defining what to build next is part of the job. The opportunity surface is large: 14 markets, 600,000 customers, a platform being rebuilt in parallel across four core engines.

Where the highest-leverage problems live right now: Dynamic pricing and margin optimization across 14 markets.

Agentic procurement: supplier selection, ordering, quality management.

Customer journey automation from configuration to post-delivery.

Intelligent content and SEO infrastructure at platform scale.

Predictive demand and inventory across the supplier network.

Internal tooling that multiplies the output of every team.

What building looks like here: No brief. You identify the opportunity, commercial case first.

You scope the solution and define the success metric before writing a line of code.

You build to production standard: monitored, tested, cost-managed.

Full lifecycle ownership. Live means live, not merged to a branch.

You measure the commercial outcome and report it as a number.

You move to the next highest-leverage problem immediately.

Who you are: The closest reference point is someone who has been building since childhood, not because anyone asked, but because you could not stop. A technical co-founder who has never had anyone to hide behind. Someone who has learned to prioritise by asking 'what is this worth?' before asking 'how do I build it?'. You do not think of yourself as an AI engineer. You think of yourself as someone who solves hard problems and builds the systems to prove it. The engineering is the method. The obsession is the identity.

Three signals that tell us you are that person: You have identified and built AI solutions without being assigned them. You saw the commercial leverage, built the solution, and shipped it before anyone validated the idea. Ask you to name one. It takes no time to find.

Everything you have shipped is in production, monitored, and depended upon. No prototypes. No internal demos. Real systems with real numbers.

You measure your own work in revenue generated or cost removed. Not in models trained, pipelines built, or features shipped. You knew the commercial value before you built it. You tracked it after.

Must-haves: You have been building things since before it was a profession: side projects, tools, systems that nobody assigned but that had to exist.

Production systems live and depended upon by a real business, built by you personally, not led or…