Drimva

Ironclad

Staff Product Manager - Procurement AI

$210K–$255K

San Francisco · Hybrid · Staff · Full-time · Posted Oct 2, 2026

Experience
5+ years of product management experience; ideally in enterprise SaaS, workflow products, procurement technology, legal technology, or adjacent business systems.

About the job

Lead product strategy and execution for AI-powered procurement experiences that help enterprise teams manage supplier relationships, contract commitments, renewals, risk, and workflows.

What you'll do

  • Own the vision, roadmap, and success metrics for Ironclad’s procurement AI product area; drive products from discovery through launch and iteration.
  • Work with customers and cross-functional teams to translate procurement and legal needs into AI-powered workflows, including defining AI quality measures and human approval points.
  • Partner with go-to-market teams on launches, adoption, and value realization.

What they ask for

  • 5+ years of product management experience; ideally in enterprise SaaS, workflow products, procurement technology, legal technology, or adjacent business systems.
  • Track record of owning products end to end, from customer discovery and strategy through launch, adoption, and iteration.
  • Deep familiarity with procurement, sourcing, supplier management, contract lifecycle management, legal operations, or a closely related domain.
  • Practical fluency with AI product development, including evaluation, data quality, retrieval or grounding, feedback loops, and human-in-the-loop controls.

Nice to have

  • Experience building procurement or spend-management products, or with legal technology and contract workflows.
  • Experience with enterprise integrations, agentic AI products, or enterprise data models and document intelligence.

Pay

$210,000 - $255,000 USD base salary; $210K – $255K USD base salary

Tools

SAP, SAP Ariba, Coupa, Zip, Salesforce

AI focus

Build AI-powered procurement workflows and experiences; define and measure production AI quality, and incorporate retrieval or grounding, feedback loops, and human-in-the-loop controls.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 5, 2026 (UTC)