Fast Facts

MagicSchool is seeking a Senior Context Engineer for AI Systems to design and optimize AI agents' capability in educational contexts, enhancing their reasoning and memory management to provide coherent assistance for educators.

Responsibilities: Key responsibilities include implementing context management systems, dynamic information retrieval, and cross-functional collaboration for AI-driven educational tools.

Skills: Required skills include expertise in distributed systems, Python and TypeScript programming, and familiarity with LLM APIs and context optimization techniques.

Qualifications: Preferred qualifications include experience with agent evaluation metrics, knowledge of educational content standards, and a solid understanding of context management for AI systems.

Location: This job is based in the USA with remote working options available.

Compensation: $160000 - $190000 / Annually

WHO WE ARE: MagicSchool is the premier generative AI platform for teachers. We're just over 2 years old, and more than 6 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.

The Role

As a Senior Context Engineer for AI Systems, you'll architect and optimize how MagicSchool's AI agents reason, remember, and operate within complex educational workflows. You'll design context management systems that determine what information our agents see, how they maintain state across multi-turn interactions, and how they retrieve knowledge without overwhelming their attention budget—ensuring reliable, coherent AI assistance for educators.

In this role you'll implement the technical foundation of how AI agents manage their "mental workspace", and ensure our agentic capabilities remain accurate and focused in classroom scenarios.

What You'll Do

Context System Implementation

• Context Architecture & Token Optimization: Design and implement context curation systems for product features that determine what information enters each agent inference step, balancing comprehensiveness with the finite attention budget of LLMs to prevent context rot.
• Task-Specific Context Management: Build memory compaction mechanisms and state management patterns that allow agents to maintain coherence within specific teaching workflows (lesson planning, differentiation, assessment creation).
• Context Monitoring & Improvement: Implement monitoring and evaluation for retrieval precision and reasoning coherence within your features. Collaborate with staff engineers and the evaluations team on measuring attention allocation and performance.

Dynamic Information Retrieval

• Just-in-Time Knowledge Retrieval: Build dynamic, runtime data fetching that enable agents to autonomously pull relevant curriculum content, student data, and educational resources exactly when needed, rather than pre-loading context with unnecessary information.

Tooling & Integration Implementation

• Tool & Integration Implementation: Build token-efficient tool APIs and retrieval layers for product teams to build context-aware features

Cross-Functional Collaboration

• Product Collaboration: Partner with Product to translate educational workflows into optimal context configurations, understanding which information signals matter most for different teaching scenarios.
• Technical Collaboration: Work with evaluations researchers, platform engineers, and others to implement memory modules, retrieval adapters, and human-in-the-loop correction systems within your team's applications.

Technical Leadership

• Squad Technical Leadership: In collaboration with Product and peers, shape work for the team. Coordinate with other squads on requirements, patterns, and integrated projects.
• Knowledge Sharing: Share context engineering insights with the team, contribute to engineering discussions on context management patterns, token budget awareness, and dynamic information curation.

What we’re looking for

• 4+ years building distributed systems. Hands-on experience with RAG systems, knowledge graphs, or semantic search platforms in production environments.
• Strong coding skills in Python, TypeScript/Node.js. Experience with our stack (TypeScript, Node.js, PostgreSQL, NextJS, Supabase) or similar. Proficiency with LLM APIs (OpenAI, Anthropic, etc.) and their context management patterns.
• Experience with Model Context Protocol (MCP), context window optimization for specific model families, or building context-aware agent frameworks.
• Understanding of or interest in how educational content is structured (standards, curricula, taxonomies), privacy requirements (FERPA/COPPA), and how context needs differ across teaching scenarios.
• Experience with agent evaluation, measuring context quality/relevance, or instrumentation for attention budget tracking.
• Knowledge of curriculum standards, learning progressions, or educational metadata schemas that inform context design.

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.
• 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.
• Plus a 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.