Backed by Greylock, NEA and Entrepreneur First.
About the role
We are looking for an experienced AI Product Manager who is passionate about building intelligent products customers love. You will join a dynamic, fast-paced environment and work with cross-functional teams — engineering, data science, design, and go-to-market — to design, build, and launch AI-powered products that deliver our company's vision and strategy.
What they're looking for
- BS/MS degree in Computer Science, Engineering, Data Science, or equivalent practical experience
- 3–5 years of proven product management experience, with at least 1–2 years owning AI/ML-powered product features in a SaaS environment
- Proven track record of managing all aspects of a successful product throughout its lifecycle — from discovery through launch and iteration
- Demonstrated ability to develop product and AI strategies and effectively communicate recommendations to executive leadership
- Solid technical background with hands-on understanding of software development, modern AI/ML technologies (LLMs, embeddings, classical ML), and SaaS architectures
- Ability to read and interpret ML model outputs, understand evaluation metrics (precision/recall, AUROC, RMSE, F1, eval sets for LLMs), and hold technical teams accountable to model quality
More about this role
We are looking for an experienced AI Product Manager who is passionate about building intelligent products customers love. You will join a dynamic, fast-paced environment and work with cross-functional teams — engineering, data science, design, and go-to-market — to design, build, and launch AI-powered products that deliver our company's vision and strategy. This role sits at the intersection of applied AI/ML, customer outcomes, and business strategy: you'll define what we build, why we build it, and how we measure success in a rapidly evolving AI landscape.
- Own the AI product roadmap — including LLM-powered features, predictive models, agentic workflows, and ML-driven automation — translating customer needs into a prioritized, outcome-driven plan.
- Develop a deep understanding of customer experience, identify product gaps where AI can deliver disproportionate value, and generate new ideas that grow market share, improve customer experience, and drive growth.
- Partner closely with data scientists, ML engineers, and software engineers to scope models, evaluate tradeoffs between accuracy, latency, cost, and UX, and ship with quick time-to-market and optimal resources.
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