Engineering Team Lead

Who you are

• 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 built container or workload platforms — orchestration, scheduling, isolation, request routing — not just deployed onto someone else's serverless platform
• Deep Linux: namespaces, cgroups, image layers, page cache — comfortable well below the application layer
• Multi-tenancy instincts: density, isolation, and fairness when hundreds of customers share one fleet
• Significant experience building complex 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 the job involves

• 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

Benefits

• Competitive bonus structure
• Equity
• Opportunities for professional growth and development