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