DevOps / Platform Engineer (AI platform)

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 operates.

We already have agents in production. What we need now is the platform underneath them to be solid, fast, and scalable.

• Our data is content metadata – no PII, no sensitive records. We can train, experiment, and deploy without the regulatory overhead that slows most AI teams down.

• Full backing from our board and PE sponsor. This is the company’s strategic bet, with real budget behind it.

• 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.

You own how the AI platform runs. Deployment pipelines, infrastructure, monitoring, scaling, cost. If the team can’t ship because something is slow, broken, or expensive – that’s your problem to solve.

• Build and own CI/CD pipelines for AI workloads

• Manage infrastructure across AWS and GPU clusters

• Own monitoring, alerting, and observability

• Handle scaling, compute allocation, and performance

• Optimize infrastructure costs

Requirements:
You'll thrive in this role if you have:

• Production-grade Python.

• Deep AWS experience and infrastructure-as-code. CloudFormation, Terraform, or similar. You design infrastructure, not just configure it.

• CI/CD expertise. You’ve built deployment pipelines for systems that can’t go down.

• Observability mindset. You’ve set up monitoring, alerting, and logging for production systems and you know what to measure.

• Experience with real-world systems – data, storage, APIs, compute. You understand the full stack underneath an application.

• AI/ML infrastructure experience. GPU clusters, model serving, inference at scale. You’ve managed the infrastructure that AI runs on.

• Hybrid cloud experience. On-prem and cloud, or multi-cloud environments.

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)