Senior Product Manager
About Playlab
Playlab is a tech non-profit dedicated to helping educators and students become critical consumers and creators of AI.
We believe that an open-source, community-driven approach is key to harnessing the potential of AI in education. AI is a new design material and should be shaped by many to bring their ideas about learning to life. We equip communities with software and hands-on learning that empowers educators & students to build AI apps for their unique context.
If you're passionate about building creative, equitable futures for students and teachers, we hope you'll join us.
The Role
This is a hands-on, high-ownership role for someone who wants to shape how educators and students build with AI.
Your product work will:
Expand what's possible: Add new capabilities (e.g., components, agents) that expands how creators craft ai native software for their contexts.
Deepen the context: Build on our current work on curriculum knowledge graphs and organizational knowledge bases to deepen how creators can leverage their context.
Set the safety standard: Push the boundaries on what responsible and safe AI in education looks like. This includes advancing our moderation and safety systems; supporting learnability, legibility, and interpretability within the product; collaborating with key ecosystem partners; and open sourcing as much of this work as we can to advance the ecosystem.
You'll work directly with our CTO, engineering team, ML team, designers, and partnerships team. You'll hear directly from educators through our deep partner relationships. And you'll make product decisions that affect how educators and learners across the globe experience AI in education.
This role requires comfort with ambiguity. Playlab is an early-stage product with significant scope, a growing team, and limited existing product process. You'll need to build that process as you go and not wait for someone to hand it to you. If you need a lot of structure to do your best work, this isn't the right fit. If you thrive when you can shape the environment around you, read on.
What You'll Do
Drive Product Execution
Prioritize ruthlessly, write clear specs, and work with design, engineering, and learning teams to ship
De-risk builds by breaking work into meaningful increments that let us learn as we go
Make tradeoffs when scope, timeline, and resources collide and communicate those tradeoffs clearly
Go Deep on the Details
Write detailed requirements that align design, engineering, and go-to-market teams
Understand the technical constraints and possibilities, and work side-by-side with engineering
Engage directly with users, and gather user feedback, usage data, and partner insights to inform decisions
Build Product Process
Establish rituals, artifacts, and communication patterns that help a growing team stay aligned
Create clarity about how product decisions get made, without slowing the team down
Document what's working so others can build on it
Collaborate Across Teams
Work with Learning and Partnerships to translate field feedback into clear priorities and simpler designs
Coordinate with design to ensure what we build is usable, not just functional
Refine Strategy as You Learn
Pressure-test strategic assumptions against what you see in the product and hear from users
Surface when priorities should shift, and make the case with evidence
Help leadership make better decisions by bringing clarity to ambiguous situations
You Might Be a Fit If You...
Have 7+ years of product management experience, including at least one early-stage or high-growth environment where you had to build process, not just follow it
Have led product development for AI-powered or technically complex products—you can work fluently with ML and engineering teams
Get energy from the details: you'd rather write a clear spec than a strategy deck
Ship fast without cutting corners: you know how to de-risk builds and make incremental progress
Thrive in ambiguity and can make good decisions with incomplete information
Communicate crisply: you can explain complex tradeoffs to technical and non-technical audiences