We are building one of Europe’s largest AI infrastructure offering that will provide our customers a private and integrated stack in every form factor they may need — from bare-metal servers to fully-managed PaaS. You will join a fast growing team to help building, scaling and automating our computing management stack. You will be responsible for building fault-tolerant and reliable infrastructure to support both our internal processes and customer platform.
What you'll do
Your primary responsibility will be to engineer robust and dependable infrastructure that supports both our internal operations and customer-facing platforms.
Key Responsibilities:
• Design, build, and operate a scalable Kubernetes-based platform to host large-scale AI and HPC workloads, ensuring high performance, reliability, and security.
• Own the full lifecycle of cluster management, from bootstrapping and provisioning to global operations, by integrating and developing the necessary software components—including automation, monitoring, and orchestration tools.
• Drive infrastructure innovation by designing workflows, tooling (scripts, APIs, dashboards), and CI/CD pipelines to optimize system reliability, availability, and observability.
• Champion a zero-trust security model, strengthening IAM, networking (VPC), and access controls to safeguard the platform.
• Develop user-centric features that simplify operations for both sysadmins and end customers, reducing friction in daily workflows.
• Lead incident resolution with rigorous root-cause analysis to prevent recurrence and improve system resilience.
What you need
• Strong proficiency in software development (preferably Golang) and knowledge of software development best practices
• Successful experience in an Infrastructure Engineering role (SWE, Platform, DevOps, Cloud…)
• Deep understanding of Kubernetes internals and hands-on experience with containerization and orchestration tools (Docker, Kubernetes, Openstack…)
• Familiarity with infrastructure-as-code tools like Terraform or CloudFormation
• Knowledge of monitoring, logging, alerting and observability tools (Prometheus, Grafana, ELK, Datadog…)
• Exposure to highly available distributed systems and site reliability issues in critical environments (issue root cause analysis, in-production troubleshooting, on-call rotations…)
• Experience working against reliability KPIs (observability, alerting, SLAs)
• Excellent problem-solving and communication skills
• Self-motivation and ability to thrive in a fast-paced startup environment
