Principal Product Manager | Prism Workflow Engine
Overview
The Workflow Engine is the shared foundation that enables reliable, reversible, auditable, and reusable work against the ERP. You define how work is represented and tracked, how information is passed between different parts of the system, and how much autonomy an AI agent gets based on the reversibility of its actions. You also own the policy, approvals, and audit trails that ensure the system is safe to use with real production data.
Responsibilities
Own the product vision and build sequence, deciding what ships first as you take the Workflow Engine from its initial build to market.
Define how work is represented and handed off, owning 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.
Own the full system, not one piece of it, being the single product owner across all of the engine's functional areas: authoring, execution, quality, and governance.
Resolve open questions with the right partners, driving resolution of technical design issues in partnership with the identity and security teams, professional services, and others.
Partner with other teams building on Prism to encourage them to use the Workflow Engine instead of building their own version, owning the onboarding experience for a team running its first workflow.
Own the outcome-based pricing model, building the financial case for this approach, and being explicit about how it affects existing pricing.
Lead customer pilots, proving 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.
Stay current on industry trends and fold what's useful into the roadmap to keep the system improving instead of other teams quietly building duplicate versions of the same thing.
Qualifications
Experience: 8+ years in product management, with a track record of shipping platform or infrastructure-style products that other engineering teams build on top of.
Technical Depth: 3+ years of experience with workflow orchestration, distributed systems, or applied AI/agent products, with real technical depth rather than purely commercial exposure.
Education: Bachelor’s degree in Computer Science, Engineering, Business, or a related field (or equivalent experience).
Workflow Orchestration Experience: Direct experience with a workflow orchestration platform (Temporal, Camunda, AWS Step Functions, etc.) is a strong plus.
Hands-On AI Experience: Practical experience with prompt engineering, retrieval-based AI systems, evaluation methods, and agent orchestration, ideally including using AI coding tools to prototype directly.
Programming Ability: 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.
Data and Integration Background: Familiarity with data pipeline concepts, knowledge graphs, and how modern AI systems connect to external tools and data.
Machine Learning Exposure: Exposure to frameworks such as TensorFlow, PyTorch, or scikit-learn is a plus.