Lead Product Manager, Agentic AI Platform

Role overview Own the product vision and strategy for an AI agent platform and its evaluation capabilities within an enterprise agreement-management environment. This individual contributor role focuses on making multi-step AI agents measurable, safe, reliable, and useful at scale, enabling more autonomous workflows while giving teams clear evidence of quality and performance.

Responsibilities - Define the roadmap and product strategy for the AI agent platform and evaluation experience. - Establish ways to measure, benchmark, and continuously improve agent quality, safety, observability, and performance. - Lead platform initiatives that support agent orchestration, AI agents, tools, and multi-step workflows. - Partner with engineering, applied AI, data, design, go-to-market, and other product teams to deliver cohesive experiences. - Engage customers to understand how they use and assess AI agents, identifying gaps and opportunities for improvement. - Instrument important workflows, use quantitative and qualitative evidence, and iterate based on adoption, usage, and product insights.

Requirements - 12+ years of product management experience, including 5+ years working with enterprise SaaS products. - Bachelor’s or master’s degree in computer science, engineering, or a related technical field. - Experience building enterprise-grade AI-powered experiences and AI agent products. - Experience defining product metrics, AI evaluation systems, experimentation frameworks, or comparable measurement approaches. - Demonstrated ability to lead complex collaboration across product, engineering, design, applied AI, data, and related functions.

Nice to have - MBA or experience managing AI platform products. - Familiarity with agreement lifecycle management, legal technology, document platforms, or document management systems. - Customer-first product practice grounded in both qualitative feedback and quantitative analysis.

Benefits and work setup Hybrid role requiring access to an office, with a weekly in-office expectation of at least two days, subject to team and local requirements.