Engineering Team Lead, Managed K8s
You will lead a team building a sovereign AI cloud and manage the Kubernetes product end-to-end. The role involves half people management and half technical architecture and coding.
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87,000+ live jobsRemote from Spain·Full-time·Added 6 days ago (last checked 12 Oct)
9 open roles
Full-time
Per the ad.
Fully remote
Per the ad.
The ad doesn’t mention sponsorship
Not a refusal, but not a yes. Worth asking in your first message.
Work in English
English is required, per the ad.
Have 8+ years of experience
Lead-level role.
Private health insurance
Per the ad: paid by the employer, or taken through flexible pay.
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.
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.
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.
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.
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.
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.
Intro conversation
With a recruiter or hiring manager
Understand your background, interests and expectations.
Role-specific interviews
Interviews with the hiring manager and team plus a case exercise for GTM and corporate roles, or a series of technical exercises for science, product and engineering roles.
Values conversation
A final discussion on alignment with Mistral's values and ways of working.
Reference checks
Mistral AI is a French artificial intelligence company founded in 2023, specializing in the development of large language models and generative AI solutions. The company has quickly become a leading European AI player, offering both open-weight and commercial models, and has established partnerships with major cloud providers and enterprises. With a global footprint, Mistral AI is headquartered in Paris and operates across multiple countries, positioning itself as a key competitor to US-based AI labs.
In Spain, Mistral AI is expanding its commercial presence, with open roles focused on the Iberian market, including enterprise sales and AI deployment strategy. The company's culture is fast-paced, research-driven, and highly technical, making it an attractive destination for international professionals with expertise in AI, machine learning, and enterprise technology. As a European champion in AI, Mistral offers the opportunity to work on cutting-edge technology while contributing to the region's technological sovereignty.
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.
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