Member of Technical Staff - Software EngineeringComp confirmed on your call.
The role
Frontier AI models are bottlenecked by data: the next generation of agents requires experiential training, learning through trial and error across real digital software. This seed-stage AI lab builds the interactive, resettable software environments that make this training possible, supplying critical training environments directly to multiple frontier labs. Founded by a repeat founder with a successful exit and backed by prominent tech angels and venture funds, they have grown to over 50 staff across London and Paris in roughly twelve months.
As a Member of Technical Staff, you will build the distributed platform underneath: the APIs, backend runtimes, persistence layers, and pipelines that generate, run, and scale dynamic environments. This role is calibrated from Mid through Principal based purely on the technical scope and architectural ambiguity you can own, not your years of experience. This is not prompt engineering, wrapper building, or workflow orchestration; it is foundational backend systems engineering turning cutting-edge agent training methods into reliable, production-grade infrastructure.
The work
- Design and operate the core backend services, APIs, and persistence layers that instantiate, isolate, and reset complex software environments on demand.
- Build distributed workflows and high-throughput pipelines to capture, process, and serve agent interaction traces directly into AI training loops.
- Partner closely with AI and curriculum researchers to translate raw experimental methods into hardened, scalable platform capabilities.
- Drive operational rigor across the engineering stack, setting standards for automated testing, observability, infrastructure as code, and continuous deployment.
What you bring
- Demonstrated track record of building, debugging, and operating distributed, data-intensive backend systems in production on AWS, GCP, or equivalent cloud platforms.
- Deep technical fluency in at least one typed language; their primary stack is TypeScript and Node.js, but background in Go, Rust, Java, C++, or similar is welcome.
- Proven history of independently owning ambiguous systems from raw problem statement to shipped production infrastructure, without needing detailed specifications.
- Committed to staying deeply hands-on in architecture, implementation, and code; this seat is not for coordinators or pure managers.
- Able to work on-site from their engineering hubs in London or Paris.
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