WHO WE ARE: MagicSchool is the premier generative AI platform for teachers. We're just over 2 years old, and more than 7 million teachers from all over the world have joined our platform. Join a top team at a fast growing company that is working towards real social impact. Make an account and try us out at our website and connect with our passionate community on our Wall of Love.
As a Senior Product Manager for AI Systems & Context, you will define how MagicSchool’s AI agents think, reason, retrieve information, and maintain coherence across complex educational workflows. You’ll translate company vision and goals into a product strategy that applies deep systems, retrieval, and knowledge-graph concepts to context, memory, and retrieval foundations that power intelligent, reliable agentic behavior for millions of educators.
Define and own the product strategy for context, memory, and retrieval systems that determine what information AI agents see, how they maintain continuity, and how they ground responses from structured and unstructured data.
Partner with Context Engineering and Knowledge Graph Engineering to translate advanced technical capabilities - dynamic retrieval, context compaction, graph-powered reasoning - into clear product requirements, evaluation frameworks, and shipped features.
Drive end-to-end development of context pipelines and AI reasoning systems to ensure products balance token efficiency, retrieval precision, and real-world classroom reliability.
Design measurement frameworks for context quality, retrieval performance, knowledge grounding, and long-horizon coherence; use these to prioritize improvements and safeguard product correctness.
Represent educators and classroom workflows with deep empathy and collaboration, defining which information and tools are needed to power effective AI assistance across lesson planning, differentiation, assessment, and complex multi-step tasks.
5+ years of product management experience, including ownership of platform, AI systems, agentic workflows, retrieval systems, or technically complex backend products.
Strong understanding of AI context management, including experience with LLMs, agent architectures, prompt strategies, context windows, embeddings, retrieval-augmented generation (RAG), memory systems, or structured knowledge representations.
Technical fluency with data systems, with familiarity in knowledge graphs, database optimization, entity/relation modeling, retrieval pipelines, and relevance/tuning concepts.
Ability to partner deeply with engineering, translating distributed systems constraints, retrieval models, and graph architectures into product strategy and requirements.
Experience using both qualitative and quantitative data (eval metrics, retrieval quality, latency, token usage, performance degradation) to drive product decisions.
Exceptional execution and prioritization skills, especially in highly technical environments with complex interdependencies across engineering, research, and platform teams.
Clear, persuasive communication skills, able to align partners across engineering, research, education, and product on highly technical concepts.
Experience shipping platform-level or AI/ML-driven systems involving context, retrieval, or structured information.
Hands-on work with LLM-based products, ideally including RAG architectures, memory systems, vector search, or dynamic retrieval.
Demonstrated experience working closely with data engineering teams, with familiarity in concepts like:
knowledge graphs
entity linking
schema design
database/query optimization
semantic search patterns
Strong background working within complex technical stacks (Python, TypeScript/Node.js, relational databases, vector databases, or equivalent).
Proven track record driving measurable improvements in system quality, reliability, or correctness.
Direct experience with knowledge graph systems, Neo4j/Neptune, graph query languages, or semantic data modeling.
Experience defining or evaluating agentic system performance, context quality, retrieval precision, token efficiency, or long-horizon coherence.
Background in hybrid retrieval systems integrating structured graph data with vector search or embedding-based retrieval.
Familiarity with educational data structures (standards, curricula, assessments, taxonomies), FERPA/COPPA requirements, or EdTech ecosystems.
Prior work in domains requiring complex relationship modeling or high correctness (finance, healthcare, enterprise search, supply chain, etc.).
Application Notice:
Notice: Priority Deadline and Review Start Date
Please note that applications for this position will be accepted until 1/4/25 - applications received after this date will be reviewed on an intermittent basis. While we encourage early submissions, all applications received by the priority deadline will receive equal consideration. Thank you for your interest, and we look forward to reviewing your application.
Why Join Us?
Work on cutting-edge AI technology that directly impacts educators and students.
Join a mission-driven team passionate about making education more efficient and equitable.
Flexibility of working from home, while fostering a unique culture built on relationships, trust, communication, and collaboration with our team - no matter where they live.
For full time employees:
Unlimited time off to empower our employees to manage their work-life balance. We work hard for our teachers and users, and encourage our employees to rest and take the time they need.
Choice of employer-paid health insurance plans so that you can take care of yourself and your family. Dental and vision are also offered at very low premiums.
Every employee is offered generous stock options, vested over 4 years.
401k match & monthly wellness stipend.
Our Values:
Educators are Magic: Educators are the most important ingredient in the educational process - they are the magic, not the AI. Trust them, empower them, and put them at the center of leading change in service of students and families.
Joy and Magic: Bring joy and magic into every learning experience - push the boundaries of what’s possible with AI.
Community: Foster community that supports one another during a time of rapid technological change. Listen to them and serve their needs.
Innovation: The education system is outdated and in need of innovation and change - AI is an opportunity to bring equity, access, and serve the individual needs of students better than we ever have before.
Responsibility: Put responsibility and safety at the forefront of the technological change that AI is bringing to education.
Diversity: Diversity of thought, perspectives, and backgrounds helps us serve the wide audience of educators and students around the world.
Excellence: Educators and students deserve the best - and we strive for the highest quality in everything we do.
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Learn more about MagicSchool AI and explore their open positions.
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