Staff Product Manager, AI Factory
Technical Product Manager owning AI governance, extensions framework, and ML lifecycle capabilities for regulated enterprise AI platforms. Requires 5+ years PM experience shipping to technical users, strong CS background, and enterprise customer ownership.
About the job
Responsibilities
- Advance our Governance feature set — embedding model validation, review and audit-readiness directly into the development lifecycle, including automated model documentation and modern takes on longstanding requirements like attestation and revalidation.
- Shape the Extensions framework, a new product surface for embedding custom capabilities into the platform: model risk management, onboarding, inventory, and audit-ready documentation.
- Lead the next generation of AI/ML lifecycle capabilities, with a specific focus on generative AI and advanced AI systems.
- Strengthen how customers deploy, host, secure and administer Domino across SaaS and customer-managed environments.
- Partner directly with customer executives — up to and including CIOs, CTOs and Chief Data Officers at Fortune 100 companies — to turn their hardest operational-AI problems into product decisions.
Requirements
- 5+ years of product management experience shipping enterprise software to developers, ML engineers, quantitative researchers, data scientists or similar practitioners — users who write code as their primary interface with the product. Non-negotiable.
- Strong technical background — computer science or an equivalent discipline — and a track record of solving hard product problems where the difficulty is intrinsic, not superficial. You operate as a peer in system design conversations, not a translator.
- Customer-first instincts. You've owned enterprise customer relationships in prior roles and are comfortable running product conversations inside large, politically complex organisations. You listen carefully, read a stakeholder map, and turn what customers actually need into product decisions.
- Execution-focused. You want to join at an inflection point, not a steady state — at your best when synthesising customer signal, market direction and technical constraint into bets that ship.
Nice-to-Haves
- Hands-on familiarity with data science / AI workflows, or experience shipping product into regulated environments.
Skills
Product Management, Enterprise Software, AI/ML, Generative AI, Governance, Model Validation, Audit Readiness, Data Science, Computer Science, System Design
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