AI Systems Engineer
Simply.TV
About Simply.TV
You probably use our data every day without knowing it. When you open a streaming app, browse a channel guide, or get a move/show recommendation – the metadata powering that experience likely comes from Simply.TV.
We provide content data to the world’s largest TV distributors, streaming platforms, and telecom operators. Billions of data points. 30+ markets across EU, US, APAC, and Latin America. ~EUR 20M ARR. 400+ people. PE-backed by Summit Partners.
The opportunity
We’re turning Simply.TV into one of Europe’s first end-to-end AI-native content data companies. Not adding an AI feature to the product – rethinking how the entire business works from the ground up.
We already have agents in production. What we need now is the infrastructure and the people to take it much further. A few things worth knowing:
• Our data is content metadata – No PII, no sensitive records. That means we can train, experiment, and deploy without the regulatory overhead that slows most AI teams down
• This has full backing from our board and PE sponsor. It’s the company's strategic bet, with a real budget behind it
• We sit on billions of structured, unstructured and labeled data points
Some of what we ship won't work. That's expected. The only way to fail here is to stop trying.
The role
6-person AI team led by our Head of AI. Flat. No middle management, no approval chains. You own what you build, and what you build goes to production.
This is an infrastructure role. You’re responsible for the infrastructure that makes our AI work at scale – how models run, how data moves, how the platform performs under load.
• System architecture, data pipelines, and backend infrastructure
• Infrastructure for running LLMs in the cloud and locally
• Performance metrics, latency, and reliability
You'll thrive in this role if you have:
• Production-grade Python
• Backend engineering experience. You’ve built, deployed, and maintained systems that handle real throughput – data, APIs, storage
• Deep AWS expertise or similar. CloudFormation or other IaC. You know how to architect on it, not just deploy to it
• Data pipeline experience
How you think
We care about how you solve problems. AI moves too fast for credentials to be the main filter.
• You start by building. When something is unclear, you write code and read docs to figure it out
• You change your mind when the evidence changes. Ego stays out of technical decisions
• Dead ends are part of the work. If that frustrates you, this isn’t the right fit
• You challenge assumptions and propose things nobody else has tried
Practicalities
- Reports to: Head of AI
- Employment Type: FTE
- Location: Copenhagen
- Type of Collaboration: On-site ( Full-time-40hrs/week)