Product Manager - Memory & Personal Intelligence

Speak•San Francisco, CA

5d•$191,000 - $315,000

About The Position

Speak is looking for a Product Lead to build the memory and intelligence layer that helps Speak know what each learner should do next. Speak's next step is not more disconnected lessons. It is a learning system with durable memory and personal intelligence: it knows what each learner should do next and makes that intelligence usable across lessons, voice, assessment, content, and reporting. This person will create the product and platform layer that lets Speak deliver the right learning experience at the right time across user memory, tutors, lessons, content, recommendations, assessments, evals, and AI systems. This starts as a hands-on Product Lead role with a clear Memory & Personal Intelligence home scope and broad company-level outcome ownership. As the area grows, management scope may become part of the path, but the first-order need is someone who can personally set product direction, integrate teams, and raise execution quality.

Requirements

6+ years of hands-on product experience, as well as Product Lead experience.
AI, ML, data, recommendations, personalization, platform, learning, or technical product experience.
Strong systems thinking and enough technical fluency to reason with engineers.
Product taste and user empathy, especially where platform decisions shape user-facing quality.
Excellent writing and ability to create artifacts that travel.
Ability to lead company-level outcomes from a Memory & Personal Intelligence home scope without drifting into abstract platform strategy.
High agency without assuming formal authority or direct reports on day one.

Responsibilities

Set Memory & Personal Intelligence product direction.
Own product architecture for longitudinal memory, personalization, sequencing, recommendations, feedback loops, and learner-state models.
Define interfaces between learning experiences, content systems, evals, AI platform, and learner-facing surfaces.
Create cross-team product clarity: principles, artifacts, product requirements, and decision frameworks that multiple pods can build against.
Build product quality loops that improve learning outcomes, trust, and team velocity.
Define the memory, learner-state model, and product interfaces that help multiple teams decide what a learner should do next.
Build the product architecture connecting assessment, content generation, voice practice, recommendations, and learner-facing next actions.
Create the instrumentation and quality loops that tell us whether personalization is improving learning, not just engagement.