Two requests can look nearly identical and be worlds apart. “See if you can find me an example of this” needs a capable system: it finds the example or it doesn’t. “Conduct a reasonable search for any and all documents responsive to this request” is a different kind of promise. Its answer spans a corpus no one will ever read end-to-end. So the system’s process, as much as its output, has to earn the trust of the professionals who rely on it.
That property is reliability. It decomposes into consistency, robustness, calibration, and safety: systems that behave tomorrow the way they did today, degrade predictably under stress, know how confident they should be, and check their own work. Before aiR returns an analysis, it validates its citations and runs internal consistency checks; when a check fails, it refuses to answer. It has refused more than a million times so far in 2026, and we count every one as a success: an error caught before it reached a user.
You’ll build for both, and set the direction for how your workstream does it.
The Focus: Public Sector Investigations
This role anchors our science for public-sector investigations: FOIA and public-records workflows, government investigations, and the agencies that run them. Records officers and investigators face the same combinatorial problem as litigators, with an added obligation: their results answer to the public. You’ll own the science for this domain end-to-end, from retrieval and review systems to the evaluation standards that make responses complete, correct, and defensible.