AI Engineer, Internal Systems
At a glance
Mid-level AI Engineering role at Wispr Flow. San Francisco · full-time · no salary stated · we estimate $183,750–$246,250.
Wispr Flow has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Build end-to-end checks so agents can judge whether a task is truly finished
- Set up fast, reliable test spaces and convert breakdowns and human input into lasting evaluation signals
- Adjust the context, instructions, skills and memory agents receive, then test which changes improve results
- Run the agent fleet as a live system and assess its quality, uptake and impact
What you bring
- You have made internal tools that other engineers adopted and can explain how you assessed their impact
- You work extensively with agentic coding tools and have clear views on their strengths and limits
- You have built evaluation or verification infrastructure, such as test harnesses, CI systems or benchmarks
- You can work hands-on with application code, infrastructure and unfamiliar systems
Who this fits
This mid-level, hands-on role suits someone who tests their assumptions, notices subtle failure modes and can take ownership of ambiguous work. The job is onsite in San Francisco. Prior experience in voice, model training or related product areas is not required.
From the employer
About Wispr
Wispr is an AI research and product company building the voice interface for computing. AI can now reason, code, and act. Yet, humans still do the work of the interface. We think that’s backwards.
Our first products are Flow, which lets you speak naturally in any application, and Notetaker, which builds context across conversations. We’re building toward an interface that can perceive, understand, and take action with earned trust. That means solving hard problems across models, systems, and product - and caring about the final human experience as deeply as the technology underneath it.
We’re a talent-dense team that holds strong opinions, tests them quickly, and builds technology that sparks joy. Our goal is to build the first voice interface used every day by a billion people.
About the role
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.
What you'll do
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.
Get to know us
Logistics
We sponsor H1B, O1, EB1, L1, STEM OPT, and more. We can't guarantee sponsorship for every role, but if we make you an offer we'll make every reasonable effort, with help from our immigration law firm.
We strongly encourage you to apply even if you don't meet every qualification. The strongest candidates we meet rarely do, so don't exclude yourself prematurely. We're rethinking how humans interact with AI, and doing that well demands diversity of perspective and experience.
We're committed to a fair and accessible interview process. If you need any accommodations or adjustments, please let us know.