The RoleProcess Intelligence is early, but already in production. The AI works, customers run it on their data, and product-market fit is real. You join at the point where the next few decisions decide whether this becomes a category.
You'll own the Process Intelligence product: what we offer, who it's for, how it's packaged, and how customers transform their businesses with it. You don't own the models or the pipeline, but you understand them well enough to know what they can detect, where they fail, and what to ask for next from the team that builds them.
This is a Hi-C role: a high-impact individual contributor seat built for someone who has run product at the Director or VP level and wants to get back to building. Same influence, same pay band as the leadership role you'd otherwise be interviewing for. No direct reports. You report to the Head of Product and work directly with the CEO. If this works, you'll have taken an AI product from first customers to a category, and you'll have done it with your own hands.
This is a hybrid role based in New York City. You'll be in the office at least two days a week (Tuesdays and Thursdays) and travel to our Belgrade office once a quarter.
What you'll do- Build the offering. What we sell, how it's packaged, what a customer sees in week one and renews for. Decide what we don't build, and make it stick.
- Set the bar for the AI. Define what a correct process reconstruction is from the customer's side, which failures matter, and the evals that measure them.
- Shape what it detects next. A handoff, a rework loop, a shadow spreadsheet, a step AI could take over. Spec it, prove the value on real data, then hand it to engineering.
- Prototype in code. Test ideas by building them, with AI, against live customer data, before anything goes on a roadmap.
- Turn inference into action. An ops lead opens the product, understands what the AI found in two minutes, and knows their first move.
You are a great fit if you have:- Been a Director or VP of Product at a B2B software company and want to get back to building
- Taken at least one product from prototype to paying, renewing customers, and can name the bets that got it there
- Product sense and simplicity in ambiguity: you know what customers need before they say it, and you turn complex ideas into simple solutions
- Shipped something with a model in the loop, and built or owned the eval that told you whether it actually worked
- Enough technical depth to understand how event streams, pipelines and model outputs fit together, prototype with AI against real data, and hold your own with the engineers and data scientists who own the pipeline
