Our agents already write code and respond to incidents around the clock, but they can't yet tell when they're done, so every loop still ends with a human checking. You'd be the first to build the verification and evaluation layer that lets them finish with confidence.

Build end-to-end verification loops that let agents determine when their work is actually complete

Create fast, reliable testing environments and turn failures and human feedback into durable evaluation signals

Improve how context, instructions, skills, and memory are delivered to agents—and measure what makes them perform better

Operate the agent fleet as a production system and measure its quality, adoption, and impact

You may be a fit if

You've built internal tools that other engineers adopted, and you can explain how you measured their impact

You use agentic coding tools deeply and have specific opinions about where they succeed and fail

You've built evaluation or verification infrastructure such as test harnesses, CI systems, eval pipelines, or benchmarks

You can work hands-on across application code, infrastructure, and unfamiliar systems

You are empirical about your own work, attentive to subtle failure modes, and comfortable owning ambiguous problems

Prior experience in voice, model training, or our product domains is not required.

AI Engineer, Internal Systems

Responsibilities

Qualification

Required

Company

Wispr Flow

More roles at Wispr Flow