Product Manager – Vendor Intelligence, Marketplace

Responsibilities

• Own the strategy and roadmap for price benchmarks and contract intelligence, turning Ramp's aggregated spend and contract dataset into the most accurate price benchmarking product on the market.
• Build the B2B marketplace primitives that let Ramp's customers discover, compare, and engage with the right vendors, and give vendors a channel to reach Ramp's buyer base with transparent, competitive pricing.
• Design "decision moments": surfaces inside Ramp that deliver the right benchmark, contract context, or vendor alternative at exactly the moment a customer is about to sign, renew, or spend.
• Partner with data science to build the extraction, normalization, and modeling pipelines that power price benchmarks, going from raw contract PDFs and spend data to unit-normalized, SKU-level intelligence a customer can act on in a negotiation.
• Define the evaluation methodology, quality bar, and feedback loops for AI-powered contract analysis, ensuring the accuracy and explainability that enterprise customers require.
• Cover the full vendor lifecycle: discovery and intake through price negotiation, contract signing, and renewal, with the right intelligence surfaced at each step.
• Develop deep understanding of how procurement, finance, and legal teams evaluate, select, and renegotiate vendors, and translate that into sharp product bets with clear customer outcomes.
• Drive cross-functional alignment on dependencies and launch readiness: GTM enablement, customer communications, compliance review, and supportability.

• BA/BS in a technical or analytical field (Computer Science, Engineering, Analytics, Mathematics, Economics, or related).
• 5+ years of product management experience, ideally with products where data quality and customer trust are the core value proposition.
• Sharp product judgment on data products and marketplaces: you understand flywheel dynamics, network effects, coverage-versus-accuracy tradeoffs, and the cold-start problem.
• AI fluency: hands-on experience building AI features, comfort with LLM-based extraction and retrieval, evaluation methodology, and human-in-the-loop design.
• Strong commercial instincts: you understand how businesses buy software, what levers drive negotiation outcomes, and why price transparency changes behavior.
• Track record building products where trust is earned over time: explainability, auditability, graceful degradation, and clear user controls.
• Comfort working in technical environments (Figma, SQL, Git) and prototyping quickly with modern AI tools (Claude Code, Cursor).
• Clear, direct communication across technical and non-technical stakeholders; ability to make a crisp case for a product bet without a deck full of slides.