Level

Mistral AIPosted 1d ago

L4

Engineering Team Lead, Managed K8s

Engineering Team Lead, Managed K8s at Mistral AI scores 80 out of 100 on AI centrality, which makes it a Level 4 role on this board.

Remote (Paris)leadFullTime

AI in this role

Lead the managed Kubernetes platform team scaling GPU-backed infrastructure for AI training, inference, and compute.

kubernetesgpus
ai-researchinfrastructurecloud-computingteam-leadershipgpu-scheduling

About Mistral

Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms.

We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.

The team

Mistral is building a sovereign AI cloud for Europe. Our customers in finance, healthcare, and the public sector run frontier models on European-jurisdiction infrastructure, and the Cloud Platform team builds the systems that make that possible — compute orchestration, Kubernetes, bare metal, storage, networking, and the datacenter fleet that runs it all.

We run it all on our own metal, our own network, our own datacenters — which means when something breaks, the fix is ours to write.

European Compute Units let enterprises commit to multi-year capacity on that infrastructure, and we are scaling toward a gigawatt of compute across Europe by 2030. You will design and ship the layer every sovereign AI deployment depends on and shape the team building it.

The Role

This is a people-leadership role from day one. You will manage the team — hiring, coaching, performance, growth paths, honest feedback — while staying close to the code: roughly half your time in architecture decisions and the hardest technical problems the team faces, the other half leading your squad. If you are looking for a senior IC role, this is not it.

You will own our Kubernetes product end to end: a metal-to-on-demand platform built on in-house infrastructure, with GPU support for training, inference, and general-purpose compute.

Kubernetes is our product, not just our platform — we run it on infrastructure we own end to end. You will decide how the control plane scales, how GPUs get scheduled, and how quickly a rack of bare metal becomes an on-demand cluster a customer can use. The decisions you make here shape how our infrastructure scales from today's footprint to a gigawatt, and how we turn frontier AI research into production systems used by millions.

This is a role for an engineer who leads from the front because that is where the work is, not because management was the next rung on the ladder.

What You Will Do

  • Design and ship the control plane. You build alongside your team and own the architecture and the hardest implementation decisions — scheduling, operators, provisioning, node lifecycle.

  • Grow the engineers, not just the software. You set the standard for ownership, remove the obstacles in their way, and coach them past their comfort zone until the work they ship surprises them.

  • Own the reliability of the Kubernetes control plane. It is the team's headline KPI. You make the calls when it breaks at 3am, and your engineers learn from how you do it.

  • Shrink the distance from metal to on-demand. Provisioning a cluster should be minutes of automation, not weeks of tickets.

  • Partner with Product Managers to set priorities, scope initiatives, and make the technical and business tradeoffs.

  • Own people management for the team: hiring, performance, growth paths, and honest feedback — the leadership work that never becomes someone else's job.

  • Define the team's processes and execution rituals as it grows.

What We're Looking For

  • 2+ years of real people leadership. You have managed engineers — hired, coached, given honest feedback, and grown them. Hands-on contribution matters here, but this role is judged on the team you build and lead, not just the code you write.

  • You have shipped production systems in Go. Not dabbled. Shipped.

  • You have run Kubernetes in anger — and ideally built parts of it: operators, schedulers, controllers. You understand what happens underneath it, and you have worked on Linux directly, not just on managed services that sit on top of it.

  • You have run GPU workloads on Kubernetes, or you are confident you can own that domain fast.

  • You think like a developer who happens to build infrastructure, not an operator who manages it. You write code other engineers depend on.

  • Extensive experience building backend or infrastructure systems.

  • You have partnered with product, design, and business teams to ship software that reached real users.

  • A low-ego, team-first mindset. We care less about your exact domain and more about whether you are the kind of technical force other engineers want to work alongside.

What We Offer

We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.

For the most up-to-date details on benefits available in your location, please refer to our Benefits page.

Privacy Policy

Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

AI ResearchInfrastructureCloud ComputingTeam LeadershipGpu SchedulingKubernetesGpus

Questions you could be asked

  1. Tell me about a research question you investigated. What did you find?
  2. Tell me about a project where infrastructure was part of your work. What did you do?
  3. Tell me about a project where cloud computing was part of your work. What did you do?
  4. Tell me about a project where team leadership was part of your work. What did you do?
  5. Tell me about a project where gpu scheduling was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI Research, Infrastructure, Cloud Computing, Team Leadership, and Gpu Scheduling. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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