Principal Product Manager | Prism Workflow Engine

Epicor • Eau Claire, WI

10d • Hybrid

About The Position

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.

Requirements

• 8+ years in product management, with a track record of shipping platform or infrastructure-style products that other engineering teams build on top of.
• 3+ years of experience with workflow orchestration, distributed systems, or applied AI/agent products, with real technical depth rather than purely commercial exposure.
• Bachelor’s degree in Computer Science, Engineering, Business, or a related field (or equivalent experience).
• Create hands on working prototypes of product concepts in addition to documentation and design.
• Strong product management fundamentals. Proven ability to validate customer needs, prioritize ruthlessly, and build a roadmap for a complex product, ideally one that other teams build on top of rather than a single customer-facing feature.
• Real technical depth in distributed systems. Working understanding of how multi-step, distributed processes are typically designed, including patterns for handling partial failure and rollback, sufficient to make real product trade-offs with an architect and a senior engineer rather than just relaying their recommendations.
• Applied AI knowledge. Strong working knowledge of AI agents, how they retrieve and use information, and how to evaluate whether they're working correctly, enough to make real architecture and trade-off decisions, not just sponsor them.
• Comfort with a fast-moving, hands-on way of working. Comfort defining clear specs and success criteria, and directing a small, cross-functional team without ambiguity about who owns what decision.
• Understanding of governance and trust. Understanding of how risk classification, approvals, audit trails, and emergency controls translate into customer trust, since that trust is the product's core value.
• Analytical and financial fluency. Data-driven decision-making, and the financial fluency to build a usage- and outcome-based pricing case and a rigorous return-on-investment model.
• Leadership without formal authority. Ability to drive alignment across peer leads in architecture, design, engineering, and quality, and across adjacent teams like security, sales operations, and professional services, without having formal authority over any of them, and to explain a clear, credible product vision to each audience.
• Familiarity with modern software delivery. Familiarity with modern, AI-assisted software delivery and cloud/SaaS platforms.

Nice To Haves

• Previous ERP experience is a plus.
• Advanced degrees are a plus.
• Direct experience with a workflow orchestration platform (for example, Temporal, Camunda, or AWS Step Functions, or something comparable) is a strong plus.
• Practical experience with prompt engineering, retrieval-based AI systems, evaluation methods, and agent orchestration, ideally including using AI coding tools to prototype directly.
• Working proficiency in a language such as Python or C#, enough to read the system's code, prototype against it, and work credibly with engineers.
• Familiarity with data pipeline concepts, knowledge graphs, and how modern AI systems connect to external tools and data.
• Exposure to frameworks such as TensorFlow, PyTorch, or scikit-learn is a plus.

Responsibilities

• Own the product vision and build sequence. Decide what ships first as you take the Workflow Engine from its initial build to market, and keep the roadmap tied to real demand from the teams that want to build on it, not to technical completeness for its own sake.
• Define how work is represented and handed off. Own the core concepts that make the system work: how a unit of work is tracked from start to finish, and how information is passed cleanly between different parts of the system so nothing gets lost along the way. These are the two things every team building on the engine depends on.
• Own the full system, not one piece of it. Be the single product owner across all of the engine's functional areas: authoring (the tools people use to build and edit a workflow), execution (running workflows and connecting them to the ERP), quality (automated testing, simulation, and health monitoring), and governance (policy, approvals, and audit trails). Make the sequencing and trade-off calls that span all of these.
• Own risk classification and approvals as a product, not a policy document. Own the system that classifies how reversible a given action is, and the framework that decides who needs to approve what, based on things like reporting structure, dollar amount, and risk level, and make sure that logic is built into the system rather than handled manually.
• Resolve open questions with the right partners. Drive resolution of open questions the technical design has already surfaced, in partnership with the right team each time: which AI agents should be allowed to take which actions (with the identity and security teams), requiring automated testing before anything reaches production, how the system should behave when a multi-step process needs to roll back partway through (with the team building Epicor's agent development platform), how far a manual “stop” should reach in an emergency, and what spending limits should exist per customer (with sales operations).
• Drive adoption across other product teams. Partner with the other teams building on Prism so they choose to build on the Workflow Engine instead of building their own version. Own the onboarding experience for a team running its first workflow on the system.
• Own the outcome-based pricing model. Own how usage is tracked and measured, and how the engine supports a shift toward pricing based on outcomes and usage rather than per-seat licensing. Build the financial case for this, and be explicit about how it affects existing pricing.
• Lead pilots with real customers. Lead the customer pilots that prove the system works on real workflows, including what happens when something goes wrong, not just the ideal case, in partnership with the professional services team, before any broader rollout.
• Stay current and avoid duplicated effort. Stay current on how other companies are approaching AI agent orchestration and workflow automation, and fold what's useful into the roadmap so the system keeps improving instead of other teams quietly building duplicate versions of the same thing.

Benefits

• Competitive Pay & Benefits
• Health and Wellness: Comprehensive health and wellness benefits designed to support your overall well-being.
• Internal Mobility: Opportunities for mentorship, continuing education, and focused career goal setting, with 25% of positions filled internally.
• Career Development: Free LinkedIn Learning licenses for everyone, along with our Mentoring Program to boost your personal development.
• Inclusive Workplace: Collaborate with a diverse team in an inclusive, global workplace that fosters innovation and celebrates partnership.
• Work-Life Balance: Policies built on mutual trust and support, encouraging time off to rest, recharge, and reconnect.
• Global Mobility: Comprehensive support for international relocations and permanent residency processes.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal