About the role
You will own the product vision, architecture, and execution for AI-driven spend management workflows, partnering with engineering and data science teams to deliver production-grade agents. You will also lead strategic conversations with Fortune 100 executives to translate complex business pain points into innovative, self-evolving product solutions.
What they look for
Requirements
The role requires 4–6 years of B2B product management experience, with a specific focus on launching agentic AI products and multi-agent systems. Candidates must demonstrate a strong understanding of AI evaluation techniques, enterprise-scale data systems, and the ability to lead technical and strategic discussions with senior stakeholders.
Full description
About Freehand
Most AI companies are building tools. We're building the worker.
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.
The Role & The Team As an AI Product Manager at Freehand- Teams for Business Spend Management, you’ll define and deliver the future of autonomous p2p workflows. You will partner with Engineering, Data Science, UX, and go-to-market teams to ship production-grade AI agents that execute and optimize complex spend workflows with precision, reliability, and explainability. You’ll work directly with CXOs at Fortune 100 companies to understand pain points and convert them into product innovations that displace traditional outsourcing, staffing and SaaS models with intelligent, self-evolving agents. This is a foundational leadership role with scope to define vision, architecture, and roadmap, and execute against it, for one of the most critical domains in enterprise automations, at the cutting edge of generative AI.
What You'll Do
- 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.
Who You Are
- 4–6years 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
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