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Staff Product Manager – AI Data Classification

Staff Product Manager – AI Data Classification

CompanyIronclad
LocationSan Francisco, CA, USA
Salary$170000 – $210000
TypeFull-Time
Degrees
Experience LevelSenior, Expert or higher

Requirements

  • 8+ years of product management experience, with a track record of shipping high-impact technical products.
  • Experience building or scaling core AI/ML capabilities. Ideally in an Enterprise Saas environment where privacy and compliance were critical considerations.
  • Strong technical acumen and ability to partner deeply with engineers, data scientists, and platform teams.
  • Proven ability to manage ambiguity, make strategic trade-offs, and operate with high ownership.
  • Excellent communication and organizational skills—you can translate between customer value and ML architecture with clarity and influence.

Responsibilities

  • Own the roadmap for core AI-powered product experiences across Ironclad, including data extraction/classification, verification flows, and natural language search.
  • Deliver meaningful customer outcomes through iterative shipping of improved models & AI performance.
  • Build foundational infrastructure for scalable model deployment, online/offline monitoring, and performance tuning.
  • Partner with AI/ML, data science, and MLOps to ensure healthy model development and rapid experimentation cycles.
  • Lead the efforts to define our approach to RAG (retrieval-augmented generation) and agent graphs, ensuring our application teams have access to the latest tools and techniques.
  • Run your team in a way that is conducive to high-velocity AI work, blending agile practices with research-centric iterations.
  • Align product vision with broader company objectives through clear storytelling, cross-functional collaboration, and consistent stakeholder engagement.
  • Drive adoption and trust in AI by co-owning user-facing education, customization experiences, and accuracy validation loops.

Preferred Qualifications

  • Bonus: experience building search products, RAG applications and/or multi-agent architectures.