Applied AI & Automation Specialist in Lisbon

We're hiring someone who loves figuring out how things work, how they could work better, and then actually building the solution.

Someone who already spends their spare time playing with LLMs, building little tools and automating annoying tasks.

Someone whose first reaction to repetitive work is "couldn't we just" automate this?.

Someone with no ego about being wrong, because being wrong fast is how you get right.

If that's you, keep reading About the role

You'll join our Applied AI team in Lisbon to find problems across the business and build the solutions: automations, AI workflows and lightweight internal tools.

Around 75% of your time will be spent building.

You'll sit down with teams across the company, understand how they actually work and spot where time is being lost.

Then you'll scope something sensible and build it.

Today we work a lot with Claude, n8n and AI-assisted coding, but we're deliberately not tied to a stack.

Sometimes the answer is an n8n workflow.

Sometimes it's a small vibe-coded tool (built quickly, with AI writing most of the code).

Sometimes another platform makes more sense.

And sometime the best solution doesn't need AI at all.

• What you'll actually do
• Understand how the business really works

You'll meet teams across Auto Europe and learn how they actually work, not how the process document says they work.

You'll map their processes and find the repetitive work, the bottlenecks and the opportunities.

Turn messy problems into something buildable

Most problems won't arrive as a clean specification.

You'll take loosely defined problems, break them into manageable pieces and scope a sensible solution with the team.

Build.

A lot.

This is where most of your time goes.

Automations, AI workflows, lightweight internal tools.

You'll use LLMs and AI coding tools to prototype fast and iterate faster.

You'll pick the tool that fits the problem, not the other way around.

Test it against the real world

Real users do unexpected things.

You'll test what you build against real scenarios and edge cases, so it holds up on a busy Monday, not just in a demo.

Measure what actually changed

Shipping isn't the finish line.

You'll check whether what you built actually made things better.

Time saved.

Errors avoided.

Work people no longer have to do.

If it didn't help, you'll say so and fix it.

Grow with a small team

We're a small team with a lot of freedom.

We find problems across the company, decide what's worth solving, scope the approach together and build.

We're learning as we go and shaping our own way of working, not following a rigid playbook.

You'll get plenty of support and coaching.

And you'll have room to experiment, suggest ideas and increasingly own problems from discovery to delivery.

Must have

LLMs: used regularly, as part of how you already work Hands-on building: automations, workflows or tools you have made yourself Nice to have (you don't need to tick every box) n8n: a big part of how we automate today

Claude: the AI we use most across the team AI coding tools: for prototyping and iterating quickly APIs, webhooks and JSON: the basics of connecting systems together SQL or scripting What you bring

Curiosity: you are good at figuring things out

Structure: you can break a messy problem into manageable pieces Process first: you understand the problem before picking the tool Comfortable with people: you talk to stakeholders and ask lots of questions

Initiative: you get moving without waiting for a detailed specification A love of learning: you enjoy trying new tools and experimenting Good judgment: you know when to keep investigating and when to ask for help