Staff Product Manager

Valence pioneers AI-first leadership coaching for large enterprises, using machine learning and natural language processing to personalize learning and development. The Staff Product Manager will own an ambiguous, strategic company-level bet from concept through adoption, set its strategy and success metrics, and drive outcomes across multiple projects. The role also involves shaping product standards, using AI and data for analysis and prototyping, and improving how the organization ships products.

Responsibilities:

• Own a strategic bet that spans multiple projects, from concept through adoption, including the metric it's accountable to
• Develop and evangelize the strategy for that bet over months, build executive conviction on it, and defend your recommendations under pressure
• Set the product taste bar across the bet: talk to customers directly, walk the flows, and hold a clear POV on what great looks like
• Design workflows where AI does the bulk of the analysis, prototyping, and synthesis, and set the verification standards that keep that work honest
• Self-serve your own answers: write your own SQL, run your own analyses in Metabase and Amplitude, prototype in Claude/Devin/Lovable when that's the fastest path to a real answer
• Improve how the org ships: planning rituals, post-launch reviews, prioritization loops, and the systemic bottlenecks nobody has owned yet

Requirements:

• 5+ years of product management experience, including a track record of owning multi-project, strategic bets end-to-end
• Evidence you can turn ambiguity into a shipped outcome: you've taken something with no playbook and made it real
• Demonstrated ability to build executive conviction and land tough no's, including upward
• A history of shipping fast on small teams, where you did the work yourself rather than directing others to do it
• Fluency with data: you pull it, model it, and use it to pressure-test your own ideas rather than confirm them
• Daily, sophisticated use of AI in your own workflow, and a clear-eyed view of where it fails: hallucinated metrics, vibe-coded prototypes, plausible-but-wrong output
• Experience developing other PMs, formally or informally
• Bonus if you've worked on conversational, LLM-powered, or agentic products, or sold into large enterprises