Founding Member of Technical Staff, AI Infrastructure

Role overview Take end-to-end ownership of AI and infrastructure problems, starting with a real user workflow and defining what a successful result looks like. This founding engineering role spans product systems, agent workflows, evaluation, inference, and operations; the focus is on delivering a dependable system that customers or internal operators can use and assess.

Responsibilities - Work from recurring user jobs, acceptance criteria, failure modes, and operating constraints. - Design and ship the full workflow, including context, tools, state, agent control, APIs, data, evaluation, and deployment. - Determine whether bottlenecks call for changes to product code, workflow design, models, retrieval, inference, or infrastructure. - Build replayable tests that cover accepted, rejected, and invalid outcomes. - Tie technical decisions to quality, latency, reliability, cost, and the customer’s ability to operate the system. - Provide durable code, documentation, runbooks, evidence, and handoffs that others can review and reproduce.

Requirements - Strong software or systems engineering judgment and a track record of shipping products or infrastructure. - Ability to turn unclear workflows into requirements, interfaces, tests, and an executable plan. - Ability to learn unfamiliar technical layers while owning correctness and operational risk. - Clear written communication, with decisions supported by code, traces, measurements, or user outcomes. - Production experience with Python, TypeScript, Go, Rust, C++, or a comparable language. - Comfort working with customers, researchers, and engineers across technical disciplines.

Nice to have - Experience with agent systems, ML infrastructure, evaluation, observability, developer tools, inference, distributed systems, or security and privacy boundaries. - Experience in early-stage or zero-to-one work.