Senior Site Reliability Engineer, Site Lead

AI companies need inference that's fast, reliable, and economical asail delivers it. We're building an enterprise-grade inference cloud for open-weight models where customers pay for the tokens they use, and we handle everything required to serve them.

Behind one OpenAI-compatible API, we pool GPU capacity from providers around the world and continuously optimize where and how workloads run. That means turning a changing mix of hardware, networks, and infrastructure into a service customers can trust.

We've raised a $32 million Series A, and we're scaling beyond trillions of tokens a day. You'll have the ownership and reach to shape how we get there.

We're hiring an Engineering Site Lead to build and lead Parasail's engineering presence in Europe. You'll recruit a strong team, establish how it works, and take ownership of critical infrastructure behind our global inference cloud.

This is a hands-on engineering leadership role. You'll help set technical direction, contribute to architecture and implementation, and develop engineers who can own complex systems in production. Your initial focus will be infrastructure and reliability: making a changing fleet of GPUs, providers, and networks operate as one dependable service.

You'll work directly with engineering leadership and infrastructure, platform, and inference engineers across regions. You'll give the European team clear ownership, connect its work to company priorities, and make collaboration across time zones effective.

• Build the European engineering team. Recruit, hire, and develop engineers with complementary strengths in infrastructure, distributed systems, and production reliability.

• Set direction and deliver. Translate company priorities into a focused roadmap, make sound technical tradeoffs, and help the team carry work from design through production.

• Stay close to the engineering. Contribute to architecture, review designs and code, and work directly on the most important technical problems.

• Scale a global GPU fleet. Lead improvements to the Kubernetes infrastructure behind provisioning, networking, storage, and deployment across providers and regions.

• Make reliability a team responsibility. Build better isolation, failover, observability, and recovery. Establish sustainable incident response and turn production lessons into stronger systems.

• Build software that runs infrastructure. Help the team automate capacity expansion, deployments, and maintenance, reducing manual work and making changes safer.

• Connect teams across regions. Establish clear ownership, useful documentation, and effective handoffs so teams can make progress across time zones.

• Shape the engineering culture. Set a high bar for technical quality, accountability, and collaboration while giving engineers room to make decisions and grow.

• Experience leading engineering teams responsible for production infrastructure or distributed systems.

• A track record of hiring and developing strong engineers, setting priorities, and delivering meaningful technical outcomes.

• The technical depth to guide architecture, challenge assumptions, and contribute directly when needed.

• Experience building and operating reliable services, with real ownership of their performance in production.

• Strong Linux fundamentals and practical knowledge of networking, storage, containers, and Kubernetes.

• The ability to write maintainable software and automation to solve infrastructure problems.

• A systematic approach to debugging problems that cross application, cluster, network, and hardware boundaries.

• Good judgment about when to move quickly, when to simplify, and where reliability matters most.

• Clear communication and experience working effectively across teams and time zones.

You may be an engineering manager who remains close to the technology, a technical lead with experience building teams, or an infrastructure leader ready to establish a new site. What matters is your ability to build a strong team and take responsibility for the systems it delivers.

• Experience establishing or growing an engineering office or regional team.

• Experience with multi-region, multi-provider, or bare-metal infrastructure.

• Familiarity with GPUs, model serving, or inference systems such as vLLM or SGLang.

• Experience building highly available services, multi-tenant platforms, or distributed data systems.

• Experience leading teams through rapid growth while maintaining technical quality and…