Platform Engineer — Senior

EggAI Technologies GmbH; United States; Teletrabalho; USD 101 000 - 135 000; Tempo integral

Resumo da oferta

EggAI Technologies GmbH is seeking a Senior Platform Engineer to design, build and operate a cloud-native platform in production. This remote EU role keeps the team small (2–6 engineers) and focuses on deep work on one project at a time.

You will own the Kubernetes platform, lead architecture discussions, and drive reliability with SLOs, observability, and cost awareness while collaborating directly with the client's engineers and infrastructure teams.

Qualificações

• 5+ years in infrastructure / platform / SRE roles.
• At least 3 of them running production Kubernetes.
• Terraform (primary), plus Helm or Kustomize.
• A major cloud in depth: AWS, GCP or Azure with cost awareness.
• CI/CD and GitOps: ArgoCD or Flux.
• Observability and reliability: Prometheus/Grafana, OpenTelemetry, SLOs, on-call.
• Scripting: Bash, plus Python or Go.
• Security as a first-class concern: secrets management and supply-chain scanning.
• Client-facing ability to engage with client architects and engineers.

Responsabilidades

• Design, build and operate the Kubernetes platform for the engagement, defined in Terraform.
• Lead architecture discussions for your part of the platform with the tech lead.
• Take ownership and chase down ambiguous problems; vocalize when things go wrong.
• Build self-service paths for delivery engineers to stay unblocked.
• Own reliability including SLOs, observability, incident response and cost.
• Collaborate with the client's engineers in daily standups, planning, retrospectives, code and design reviews.

Conhecimentos

Client-facing ability

Platform thinking

Reliability mindset

Written communication

Ferramentas

Kubernetes

Terraform

Helm

Kustomize

ArgoCD

Flux

Prometheus

Grafana

OpenTelemetry

Bash

Python

Go

AWS

GCP

Azure

Descrição da oferta de emprego

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