Staff AI Operations Lead

About the problem space

AI has changed what's possible in go-to-market, support, and business operations. The constraint is no longer "can we build it" — it's "can we deploy it into a real workflow, prove it made things better, and keep it working."

Most companies are stuck at the demo stage: a lot of clever prompting, very little that runs reliably on Tuesday morning without someone watching it. This role exists to get us past that, everywhere outside of engineering.

Little more about the team:

You'll sit on the Data team, which is where this work belongs. Our team already operates at the seam between the business and its systems — we partner daily with RevOps, Customer Success, Sales, and Product, and we own the data infrastructure these workflows depend on. AI-in-the-business is a data problem with a model attached, and you'll have the pipelines, the warehouse, and the domain relationships already in place.

You are a senior individual contributor. Your job is to take business workflows that are slow, manual, or inconsistent, and make them fast, automated, and measurably better — then do it again, and leave behind enough shared scaffolding that the third one is easier than the first.

Ship automated workflows end to end

• Partner with department leaders to identify the highest-leverage workflows in their orgs, and go deep enough on how the work actually happens to know where a model helps and where it doesn't.
• Define success before you build: cycle time, quality, cost, risk. Instrument it. Report on it honestly, including when the answer is "this didn't work."
• Deliver working systems, not prototypes, with evaluation harnesses, human-in-the-loop review where the stakes call for it, and ongoing monitoring.
• Iterate on adoption the way a product manager would: user research, documentation, and a real plan for getting people to use the thing.

Build the shared substrate as you go

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