DevOps / Platform Engineer, English

Role Overview

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.

Tech Stack

• AWS
• Cloud
• Python
• Terraform