(Senior) Infrastructure Engineer (all genders)

Your Responsibilities

• Own and Evolve Our Infrastructure – You take ownership of our AWS and Hetzner environments and evolve them further – everything as Infrastructure as Code, running, scaling, and upgrading our Kubernetes clusters along the way

• Operate Our Platforms – You keep our webapps, self-hosted tools, and ML stack running in stable, secure production environments, with solid monitoring, logging, and alerting across systems – including observability for LLM-based workloads

• Keep Us Secure and Compliant – You handle patching, secrets management, access control, and backups, and support audits and certification efforts as part of your routine work

• Build Paved Roads for Engineers and Data Scientists – You provide the containerization, CI/CD, and deployment tooling that let both teams ship and run their own services – from webapps to RAG pipelines – enabling rather than taking over, as deployment stays a shared responsibility

Your profile

• Production-Grade Cloud Experience – You bring strong hands‑on AWS experience (EKS, RDS, EC2, IAM, networking) and are open to hybrid setups including bare‑metal/VPS providers like Hetzner

• IaC and Kubernetes as Your Craft – Infrastructure as Code is your default working mode (OpenTofu/Terraform), backed by solid scripting skills (e.g. Bash, Python) and confidence troubleshooting Kubernetes in production

• Fluent in the ML/LLM Ecosystem – You're conceptually familiar with RAG architectures, vector databases (e.g. Qdrant), and ML tooling (e.g. MLflow, Langfuse) – enough to speak the data scientists' language and support their infrastructure needs; deep hands‑on ML engineering is explicitly not required

• Enabler Mindset, Pragmatic Approach – You share knowledge through pairing, reviews, and reusable templates, explain trade‑offs clearly to any audience, prioritize autonomously, and choose "good enough" over over‑engineered