Engineering Team Lead, Fleet Delivery

Mistral.ai·Parislead

In short

→Liderazgo técnico en la entrega de infraestructura de datos a gran escala para IA soberana en Europa.
→Construyes y lideras un equipo desde cero para automatizar la puesta en marcha de servidores, racks y clusters con Go.
→Objetivo clave: reducir el tiempo de aceptación de racks de semanas a horas, a escala gigawatt.

Willing to travel to datacenter sites when the work demands it.

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What they ask for

✓8+ años construyendo sistemas backend o de infraestructura.
✓Al menos 2 años liderando equipos técnicos con contratación y desarrollo de ingenieros.
✓Experiencia probada en automatización de fleets bare-metal y entrega de racks.
✓Conocimiento profundo de Linux y experiencia en producción con Go.
✓Fluidez con hardware: servidores, GPUs (H100, GB200), NICs, switches, firmware.
✓Disposición para viajar a centros de datos cuando sea necesario.

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GoKubernetesBare metalInfiniBandRoCEFirmwareNetworkingStorageCompute orchestrationDatacenter fleet

Who should you write to at Mistral.ai?

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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. 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 A datacenter is not a cloud until software makes it one. You will lead the team that turns arriving hardware into accepted clusters. Cabling validation, burn-in, firmware, deployment validation, software stack install — all of it automated, none of it click-ops. Your KPI is time to acceptance: the hours between a rack being physically installed and it serving customer workloads. Across the industry that number is measured in weeks. You will drive it toward days, then hours, as we scale toward a gigawatt of compute across Europe. This is a founding leadership role at the intersection of hardware and software. Early on it is deliberately hands-on: most of your time in the code and the architecture, some of it on datacenter floors, because the automation has to survive contact with the machines it runs on. But the job is building and leading a team from day one — hiring your first engineers, coaching them, setting their growth paths, and running the rituals that keep quality high. As the team grows, the balance shifts toward people leadership, and you decide how fast. You shape this new team's charter and set the standard for how every future Mistral datacenter comes online. What You Will Do Build the delivery pipeline in Go: provisioning, configuration, validation, burn-in, network bring-up, software stack install. Build the team from scratch: make the first hires, onboard and coach them, own their performance and growth paths — and set the tooling standards and the playbook every future site reuses. Own time-to-acceptance and drive it down relentlessly — measure it, break it down, kill the slowest step first. Work shoulder-to-shoulder with Hardware Design and Fleet Health — reliability starts at delivery. Handle GPU fleets at scale: H100 and GB200-class nodes, InfiniBand and RoCE fabrics, and the failure modes they bring. Partner with Product Managers and the datacenter org to plan delivery waves against capacity commitments. What We're Looking For You have automated bare-metal fleets — you have written the software that turns racks into clusters. If you have done it by hand, you resented it and scripted it. Hardware fluency: servers, GPUs, NICs, switches, firmware — you can read a parts list and a topology diagram. 8+ years building backend or infrastructure systems, with at least 2 years leading engineers — real people leadership: you have hired, coached, and grown engineers, not just set technical direction. Deep Linux: you are comfortable well below the application layer. You have shipped production systems in Go. Not dabbled. Shipped. Willing to travel to datacenter sites when the work demands it.

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