Learning Commons

Product Marketing

• Develop clear, concise, and compelling positioning and copy that articulates the value and differentiation of Learning Commons AI infrastructural products
• Align messaging across research, product, and communications teams to ensure clarity and consistency across all touch points
• Stay ahead of AI and educational market trends and competitive activities to ensure relevance and resonance
• Partner with product and engineering teams to create technical demos, video scripts, and how-to materials that illustrate product functionality and use cases
• Support onboarding, documentation, and go-to-market efforts that help EdTech developers integrate or build with Learning Commons tools
• Develop messaging frameworks and value propositions for developer-focused products (e.g., APIs, datasets, evaluations)
• Shape Learning Commons’ presence at industry conferences, panels, and convenings
• Develop event strategy, talking points, and marketing materials that reinforce our brand and product narrative around our philanthropic EdTech mission
• Partner with speakers, developers, and external collaborators to ensure alignment and impact
• Measure ROI and performance of campaigns and events
• Translate complex educational research and technical concepts into accessible and engaging content for multiple audiences
• Support creation of blogs, case studies, website copy, newsletters, and product updates that bring our mission and tools to life
• Collaborate with comms, applied learning science, and product teams to maintain a consistent tone and brand voice
• Create clear and compelling recruitment and enablement materials for EdTech partners, researchers, and district leaders
• Collaborate with partnerships, product, and brand teams to ensure all collateral supports user education, adoption, and engagement

Product Marketing Manager

Product Manager

• Execute platform roadmap and sprint planning – Prioritize platform features and technical investments based on internal customer needs, working closely with engineering to plan and execute 2-week sprints using agile methodologies.
• Build strong internal customer relationships – Conduct regular discovery sessions with Knowledge Graph, Evaluators, and Developer Experience teams to understand their platform needs, gather feedback on MVP features, and iterate rapidly.
• Ship platform capabilities iteratively – Launch and refine Identity/Auth, API Gateway, MCP server, and observability features through frequent releases; track adoption and identify blockers to internal team migration.
• Define platform success metrics and SLAs – Establish metrics for platform health, reliability, adoption, and internal customer satisfaction; create service level expectations and support processes for platform issues.
• Enable cross-team platform adoption – Collaborate with 5 product managers across the organization to ensure platform capabilities meet their needs; document APIs, auth flows, and platform services for internal consumption.

Product Manager – Platform

• Own the annotation-to-evaluator pipeline: Manage the end-to-end process from identifying pedagogical constructs through dataset creation, model training, and evaluator validation; balance accuracy requirements with delivery timelines
• Shape evaluator roadmap and prioritization: Conduct discovery with EdTech developers building literacy and content generation tools to understand which evaluators deliver the most value; provide input on prioritization based on impact, feasibility, and strategic alignment
• Make strategic tradeoffs between accuracy and velocity: Partner with data scientists to set appropriate accuracy thresholds for different evaluator types; decide when to ship, iterate, or restart based on performance against baselines
• Translate learning science into product specifications: Work with learning scientists to convert pedagogical frameworks for literacy instruction into clear, measurable evaluation criteria; write detailed specs that guide annotation and model development
• Optimize and scale the annotation workflow: Identify opportunities to improve annotator efficiency, reduce ambiguity in guidelines, and increase inter-rater reliability; document learnings to enable expansion into new subject areas