Platform Engineer — Senior

EggAI · Full-time · Remote (EU only) THE ROLE A Senior Platform Engineer with deep, hands-on experience designing and operating cloud-native platforms in production. You will work in a team of 2 to 6 engineers on a client project — one project at a time, so you go deep rather than spreading yourself across accounts. Clients come to us because we work at the forefront of AI in the enterprise; you build and run the platform their AI systems actually land on, alongside their own infrastructure engineers. WHAT YOU'LL DO - Design, build and operate the Kubernetes platform for the engagement, defined in Terraform — you own it in production, not just at handover - Lead architecture discussions for your part of the platform, with the tech lead supporting you - Take ownership: pick up the ambiguous problem, chase down the answer, and say so when something is going wrong - Build the self-service paths the delivery engineers use, so they aren't blocked on you - Own reliability for what you run — SLOs, observability, incident response, cost - Work directly with the client's engineers, in a normal team rhythm: daily standups, planning, retrospectives, code and design review WHAT WE'RE LOOKING FOR - 5+ years in infrastructure / platform / SRE roles, at least 3 of them running production Kubernetes — cluster design and operation, workload lifecycle, RBAC, secrets, multi-tenancy - Infrastructure as Code in production: Terraform (primary), plus Helm or Kustomize — owned over time, not written once - A major cloud in depth (AWS, GCP or Azure): networking, compute, managed databases, IAM and least-privilege, and a habit of watching what it costs - CI/CD and GitOps: building pipelines and running ArgoCD, Flux or equivalent - Observability and reliability: metrics, logs and tracing (Prometheus/Grafana, OpenTelemetry or similar), SLOs, and on-call incident response - Scripting and tooling: Bash, plus Python or Go - Security as a first-class concern: secrets management, supply-chain and vulnerability scanning - Client-facing ability: can hold a technical conversation with a client's architects and engineers Desired qualities - Platform-thinking mindset: builds for internal customers, not just operations tasks - Pragmatic about trade-offs between reliability, cost, and engineering velocity - Thinks about blast radius before shipping - Clear written communication — design docs, trade-offs, post-incident reviews Nice to have - Service mesh, multi-cluster or multi-region experience - Consulting or professional-services background - AI/ML or agentic workloads in production - EU sovereign cloud, data residency or public sector infrastructure experience