Director of Product Management | Agentic AI

Strategic Direction & Roadmap

Own the vision and multi-year roadmap for Prism as a platform, its core agents, and its architecture. Sequence the roadmap with explicit dependencies across the data foundation, governance, and the ERP, and decide what ships first.

Build the Core

Own Prism's core agents, the agent framework, and the architecture that lets agents act safely and scale: retrieval, ontology, the execution and governance model, and the surfaces other builders depend on.

Scale the Platform (1-to-100)

• Make Prism a platform other teams build on. Own developer experience, golden paths, self-service onboarding, SDK/framework surfaces, extensibility, and the adoption metrics that prove it is working.
• Enable internal Epicor teams (Agent Foundry) and customers/partners (bring-your-own and custom agents) to build, and prevent duplicate, one-off builds.

Outcome-Based Monetization & ROI

Help move Prism's commercial model from seat-based pricing toward usage- and outcome-based pricing (pricing the work, not the seat), including how platform usage and agents built on Prism are metered. Build the willingness-to-pay, value, and ROI analysis behind it, and be explicit about cannibalization trade-offs.

Governance as Product

Treat approvals, policy, audit trails, reversibility, identity, and multi-tenant safety as product capabilities, for Prism's own agents and for everything built on the framework. Make "responsibility as moat" operational in the roadmap.

Frontier-Team Leadership

• Lead small, agent-augmented teams. Direct agent fleets against governed guardrails, hold clear decision rights, and protect the expert nuclei (architecture, evals, data, reliability) that make broad ownership sustainable.

Quality by Design

Shift quality left. Define acceptance as eval evidence and outcome metrics captured in the workflow, not as a late gate, and ship that discipline as part of the framework so teams building on Prism inherit it.

Go-to-Market & Developer Enablement

• Partner with Product Marketing on go-to-market for the platform and the agents: reference customers, beta programs, sales and developer enablement, demo kits, and field narrative, leading with proof and risk absorption, not hype.

Customer & Developer Advisory

Lead advisory engagement with both end customers and the internal/partner developers building on Prism, validate direction, and design the proactive, adoption-driving success model that AI platforms require, with continuous ROI demonstration.

Trend Monitoring & Reuse

Stay current on agentic AI, retrieval, evals, ontology, and MCP-era integration (client, server, and control-point positioning). Fold emerging capability into the roadmap and the shared catalog so the portfolio compounds instead of duplicating.

Knowledge, Skills & Abilities

• Expert Product Management: Proven command of customer validation, prioritization, lifecycle management, and strategic roadmapping for complex products.
• Platform & Ecosystem Product Management: Demonstrated skill building products that other builders build on: developer experience, APIs/SDKs, extensibility, golden paths, and adoption, with the judgment for what to centralize versus leave local.
• Applied AI Acumen: Strong working knowledge of LLMs, RAG/retrieval, agents and agent orchestration, evals, and AI UX, enough to make architecture and trade-off decisions, not just sponsor them.
• Agentic Ways of Working: Comfort operating in a spec/eval/control-plane model, directing agent fleets, and prototyping directly. Familiarity with role convergence across Product/Dev/UX/Data Science and how to make broadened ownership work without role ambiguity.
• Analytical & Financial Expertise: Data-driven decision-making and the financial fluency to build usage/outcome pricing and rigorous ROI cases.
• Governance & Trust: Understanding of how identity, auditability, controls, and reversibility translate into customer trust and competitive defensibility, for a platform that hosts others' agents as well as your own.
• Leadership & Communication: Ability to lead converged, cross-functional teams and to communicate a clear, credible, non-hype platform vision to executives, customers, builders, and the field.
• Agile & SDLC + Cloud/SaaS: Familiarity with modern, AI-assisted delivery, shift-left quality, and scalable SaaS / cloud platforms. Previous ERP experience is a plus.

Required Qualifications

• Experience: 12+ years in product management with a track record of launching and scaling technology products, preferably in AI, machine learning, or related fields.
• AI Domain Depth: 4+ years of specialized experience in the AI domain, with demonstrated technical and market understanding.
• Education: Bachelor's degree in Computer Science, Engineering, Business, or a related field (or equivalent experience). Advanced degrees (MBA, Master's in AI/ML) are a plus.

Additional Qualifications

• Platform / Ecosystem Product Experience: Shipped developer-facing platforms, APIs/SDKs, or extensibility frameworks that internal or third-party teams built on, with adoption to show for it.
• Hands-On Agentic Tooling: Practical experience with prompt engineering, RAG, evals, and agent orchestration, and ideally with agentic coding tools used to prototype and ship.
• Programming Skills: Working proficiency in a language such as Python or C#, enough to read, prototype, and validate approaches with engineering and to direct agents credibly.
• Data & Integration Exposure: Familiarity with ETL / data-pipeline concepts, ontology/knowledge-graph thinking, and the MCP-era integration landscape.
• ML Frameworks: Exposure to frameworks such as TensorFlow, PyTorch, or scikit-learn is a plus.