Principal Product Manager | Prism Workflow Engine

Overview Every product built on Prism eventually needs to do real, multi-step work against the ERP, not just retrieve information. The Workflow Engine is the shared foundation that makes that a customer's quote to cash work via AI systems reliable, reversible, auditable, and reusable. You own the product definition of that foundation: how a unit of work is represented and tracked from start to finish, how information is handed off cleanly between different parts of the system, how much autonomy an AI agent gets based on how reversible its action is, and the approval, policy, and audit systems that make the engine safe to point at real production data. This is a foundational product role. You will take the Workflow Engine from its initial build through to market launch: deciding what ships first, resolving key open questions about how the system should behave, and building the case for the resources needed to get there. Epicor Epicor is a technology leader in ERP software for manufacturing, distribution, and retail, with deep roots in both enterprise software and startup culture. Our product organization is in the middle of a deliberate move to a platform-first, AI-enabled delivery model: building shared capabilities that many teams can build on, broadening how roles work together, and removing the silos and handoffs that slow good teams down. How This Team Works The biggest change versus a traditional PM job is how the work gets done. We expect this leader to operate fluently in the model below, and to help the rest of the org adopt it. - Built as a platform, not a feature. The Workflow Engine is built for the other product teams, consulting teams, and customers that will build on it. Ease of adoption, reuse of shared building blocks, and a clear path for a new team to get their first workflow running are treated as first-class goals, not afterthoughts. Success is measured by how much operational work in the ERP is done via the workflow engine vs. manually. - A small, senior team, not a feature factory. Delivery happens in a lean, senior, cross-functional team working closely together against a system with built-in human oversight. You are inside that loop as the product decision-maker, not reviewing status from the outside. - Roles blur on a team like this. The lines between product, engineering, design, and architecture blur on a team this size. You work directly in specs, cross-team sequencing decisions, and pilot results, not a backlog handed over a wall. You keep clear ownership of product scope and decisions while picking up adjacent work that a small team requires. - Responsibility is the differentiator. How reversible an action is (fully reversible, reversible within a limited window, or effectively permanent) determines how much autonomy an AI agent gets to take it. Policy, approvals, and a clear audit trail are product features you own, not compliance add-ons, because they're what let a customer trust the system with real business decisions. - Share openly. Open questions, pilot results, and test outcomes are shared across the org so people can see clearly what the engine can and can't yet promise. What We'd Love to See Empathy for two different customers. Real understanding of the end customer whose order, supplier requalification, or month-end close runs through the engine, and of the engineering teams deciding whether to build on it or build around it. You validate both before committing to a build. A platform mindset. You think about ease of adoption, reusable building blocks, and how many teams choose to build on your system the way a good platform product manager thinks about retention, not the way a feature team thinks about a single roadmap. Working Backwards: Demonstrates mastery of cu