Engineering Manager, Serverless Containers

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.

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.

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 lead the team building our serverless containers product: the way developers run AI apps, MCP servers, APIs, and managed workers on our cloud without thinking about servers. Push a container, get an endpoint, scale from zero to thousands of instances and back down — across CPU and GPU.

On a hyperscaler, the serverless layer is a product someone else built. Here you own it end to end: the scheduler that decides where a container lands, the routing path a request takes, the machinery that turns a scaled-to-zero service into a warm instance before a customer notices. All of it runs on metal, network, and datacenters we own.

That tension is the product: scale-to-zero economics with cold starts in milliseconds, autoscaling that absorbs a launch spike without a config change, GPUs scheduled onto containers the way other platforms schedule CPU. The customers betting on this layer are the developers building the next generation of AI software on European infrastructure.

• Own the container platform end to end: image delivery, placement, request routing, scale-up, scale-to-zero — across CPU and GPU.
• Make cold starts a solved problem: snapshotting, prewarming, image-layer caching, whatever it takes for scale-from-zero to feel instant.
• Treat AI workloads as the normal case: GPU-backed containers, streaming responses, long-lived connections, MCP servers that cost almost nothing while idle.
• Write Go alongside your team and own the architecture and the hardest implementation decisions.
• Grow the engineers, not just the software — set the standard for ownership and coach people past their comfort zone.
• Own people management for the team: hiring, performance, growth paths, and honest feedback.
• Partner with Product Managers to turn platform decisions into a product developers want to deploy on.

• 3+ years of real people leadership. You have managed engineers — hired, coached, given honest…