AI Product Manager (US)

Freehand

11d•Remote

About The Position

Freehand's AI agents replace the human decision-making and coordination layer that sits above enterprise software — handling the analysis, negotiation, prioritization, and execution that previously required armies of logisticians / supply chain professionals. Our customers include Apple, Meta, GE, Pfizer, J&J, Schlumberger, Cardinal Health, and Unilever. They chose us because we have a fundamentally different answer to what enterprise software looks like when AI can do the job. If you want to work on something that matters, with people who will push you to be sharper than you thought you could be, this is the place.

Requirements

4–6 years in B2B product management with at least 2 years working on first products
Experience launching agentic AI products involving: Multi-agent systems with explicit roles & policies mirroring enterprise auth
Strong understanding of AI evaluation techniques (factuality, grounding, latency, hallucination minimization) and methods for improving agent accuracy and reliability in production.
Proven experience working with enterprise-scale data systems — invoice data, procurement records, contract metadata, FX/tax engines — with deep appreciation for governance, sensitivity, and compliance

Responsibilities

Own product vision, architecture, and execution for Freehand’s AI Teams for Spend Management across key use cases: Invoice validation & matching, Vendor onboarding & collaboration, Contract and compliance management, Dispute resolution, Cross-border payments & remittance
Define agent design patterns—multi-capability prompting, tool orchestration, retrieval pipelines, fallback logic, and policy hierarchies—that balance accuracy, reliability, and real-world business context.
Ensure end-to-end observability, including agent health, performance monitoring, confidence scoring, and auditability of decisions.
Partner with AI/ML and data eng teams to build closed-loop training pipelines and eval sets that drive continual improvement via human-in-the-loop feedback, signal instrumentation, and structured reasoning.
Drive high-fidelity UX for AI interactions, enabling explainable, proactive, and intuitive agent experiences across interfaces (UI, email, chat, APIs).
Lead technical conversations with enterprise architects and strategic conversations with CFOs, CIOs, and Chief Procurement Officers at Fortune 100 companies.
Author clear, actionable documentation (PRDs, solution briefs, agent blueprints) and deliver compelling product demos to internal and external stakeholders.