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Staff Product Manager – AI Data Classification
Company | Ironclad |
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Location | San Francisco, CA, USA |
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Salary | $170000 – $210000 |
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Type | Full-Time |
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Degrees | |
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Experience Level | Senior, Expert or higher |
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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.