Staff Platform Engineer

deepl

Deutschland

Hybrid

EUR 110.000 - 150.000

Vollzeit

Vor 3 Tagen
Sei unter den ersten Bewerbenden

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Zusammenfassung

DeepL is building a secure, intelligent AI platform and invites engineers to join the Hybrid Platform Engineering track. You will own the compute infrastructure, spanning on-prem GPUs and AWS, and help scale the hybrid model with robust incident response and platform reliability.

You will design, implement, and operate production-grade Kubernetes clusters, define IaC standards, and mentor teams to raise technical bar across the group. This role blends cloud, on‑prem, and research workloads.

Qualifikationen

  • Deep, hands-on Kubernetes expertise in production environments.
  • Experience with cloud and on-prem hybrid infrastructure.
  • Strong Linux networking and debugging skills.
  • Proficiency in Go or Python.

Aufgaben

  • Own reliability, capacity and cost efficiency of the hybrid compute platform.
  • Design and operate production-grade Kubernetes clusters across cloud and on‑prem.
  • Drive cross-team work to unify workloads across on-prem and AWS.
  • Lead incident response and improve observability and security.

Kenntnisse

Kubernetes
AWS
Linux
Networking
Go
Python
GitOps
ArgoCD
Terraform
Incident management

Tools

ArgoCD
Terraform

Jobbeschreibung

Meet DeepL

DeepL is a global AI product and research company focused on building secure, intelligent solutions to complex business problems. Over 200,000 business customers and millions of individuals across 228 global markets today trust DeepL's Language AI platform for human-like translation, improved writing and real-time voice translation.

Founded in 2017 by CEO Jaroslaw "Jarek" Kutylowski, DeepL now has around 1,000 passionate employees and is supported by world-renowned investors including Benchmark, IVP, and Index Ventures.

Our goal is to become the global leader in trusted, intelligent AI technology, building products that drive better communication, foster connections, and create a meaningful impact. To achieve this, we need talented people like you to join our journey. If you're ready to shape the future of AI and grow your career in a fast-moving, purpose-driven environment, DeepL is your next destination.

What sets us apart

What sets us apart is our blend of cutting-edge AI technology, meaningful work, and a culture where people truly thrive. We're a team of innovators, researchers, and creators driven by a shared purpose to unlock human potential by making work simpler, smarter, and more connected.

When we share what it's like to work at DeepL, the reactions are overwhelmingly positive. This might be because of our technology that helps millions of people and businesses communicate and work better every day, or because of the trust, curiosity, and care that shape our culture.

What we know for sure is this: being part of DeepL means joining a team dedicated to innovation, growth, and well-being. Discover more about life at DeepL on LinkedIn , Instagram , and our Blog .

Meet the team behind this journey

You will join the Hybrid Platform Engineering track, which builds and operates the compute layer underpinning DeepL's products and research: the Kubernetes control plane, node lifecycle, networking, storage and core cluster services, across both on-prem and cloud infrastructure. Today that spans hybrid infrastructure in Europe - including large on-prem GPU clusters powering DeepL's research and hundreds of on-prem GPU nodes serving production inference - as well as AWS regions across the globe running the product. The track is deepening this hybrid model, unifying how workloads run across on-prem hardware and AWS to give product and research teams a self-service foundation they can build on.

Your responsibilities
  • Take ownership of the reliability, capacity and cost efficiency of DeepL's compute infrastructure, CPU and GPU: the hybrid platform serving our products across AWS and on-prem, and the on-prem clusters powering our research, including their hardware lifecycle
  • Shape the platform's architecture: bring strong technical positions, weigh them on their merits with your peers, and commit to decisions serving the best outcome
  • Design, build and operate production-grade Kubernetes clusters across cloud and on-prem infrastructure, taking them from design through to long-term operation
  • Drive the technical work of deepening the hybrid model - unifying how workloads run across on-prem hardware and cloud, especially AWS and supporting research as it adopts cloud-native technology and ways of working
  • Define infrastructure-as-code and platform standards that hold across the track, and strengthen observability and security so the platform's behaviour is legible to the teams that depend on it
  • Mentor engineers across the infrastructure track and raise the technical bar of the group, through design reviews, architecture decisions and the everyday habits that keep the platform maintainable
  • Build consensus across engineering teams and turn it into shipped change, shaping platform direction at track level
  • Lead incident response for hybrid infrastructure, driving remediation through to root cause, and help sustain an on-call rotation the team can carry for the long term
What you bring to the table
  • Deep, hands-on Kubernetes expertise: you have designed, built and operated clusters at scale, through their full lifecycle
  • Depth at scale in either public cloud or on-prem infrastructure, plus the credibility to work in the other. AWS experience is preferred, and bare-metal or data centre experience is strongly valued
  • Networking and Linux depth you can debug with: you can follow a problem from a container through the host to the network edge
  • Infrastructure as code with Terraform or equivalent, and GitOps delivery with tooling such as ArgoCD, applied to environments you have owned in production
  • Software engineering skills in at least one major language, Go or Python preferred, at the level of building tooling other engineers rely on
  • A track record of technical ownership spanning several teams: you create clarity where a mandate crosses team boundaries, hold clear technical positions, change them on evidence and carry other engineers with you
  • Strong incident-management and reliability-engineering discipli
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