[Hiring] Senior Platform Engineer @EggAI

Role Description

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.

• 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.

Qualifications

• 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.

Company Description

EggAI is an enterprise-focused generative AI company on a mission to help large organizations move AI solutions from prototyping into production. We specialize in building safe, reliable, and scalable AI systems that deliver real business impact.

We work at the cutting edge of AI technology, implementing agentic systems, RAG (Retrieval-Augmented Generation) architectures, and autonomous AI agents that scale from task automation to workforce automation. Our proprietary frameworks—including the EggAI Meta Framework for agentic systems and EggAI Quality Flow for governance—power AI transformations at enterprise scale.

Based in Munich, Germany, we work with enterprise clients to build AI capability, deliver production-ready systems, and establish quality-controlled AI operations.