Fast Facts

MagicSchool is seeking a Staff Context Engineer in AI Systems to architect and optimize AI agents for educational workflows, impacting millions of educators globally.

Responsibilities: Responsibilities include designing context management systems, building dynamic information retrieval mechanisms, and collaborating with cross-functional teams to enhance AI agent functionalities.

Skills: Required skills include deep systems experience, expertise in context engineering, and proficiency in Python and TypeScript/Node.js.

Qualifications: Preferred qualifications include experience with educational technology and insights into educational content structuring, privacy requirements, and context-sensitive AI workflows.

Location: USA

Compensation: $205000 - $240000 / 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 Staff Context Engineer for AI Systems, you'll architect and optimize how MagicSchool's AI agents reason, remember, and operate across complex educational workflows. You'll design the context management systems that determine what information our agents see, how they maintain state across multi-turn interactions, and how they dynamically retrieve knowledge without overwhelming their attention budget ensuring reliable, coherent AI assistance for millions of educators.

This is a high-impact IC role where you'll define the technical foundation of how AI agents manage their "mental workspace," mentor engineers on context engineering principles, and ensure our agentic capabilities remain accurate and focused even in extended, complex classroom scenarios.

What You'll Do

Context Pipeline Architecture

Context Architecture & Token Optimization: Architect and implement adaptive context curation pipelines that determine what information enters each agent inference step, balancing comprehensiveness with the finite attention budget of LLMs to prevent context rot.
Long-Horizon Task Management: Invent and operationalize memory compaction mechanisms and state management patterns that allow agents to maintain coherence across extended teaching workflows (lesson planning, differentiation, assessment creation).
Context Evaluation & Monitoring: Design evaluation pipelines that measure retrieval precision, token relevance, and reasoning coherence as context evolves across sessions. Work with the evaluations team on developing frameworks for measuring attention allocation and agent performance degradation.

Dynamic Information Retrieval

Just-in-Time Knowledge Retrieval: Build dynamic, runtime data fetching systems 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 Design

Tool & Integration Design: Engineer token-efficient tool APIs and retrieval layers where each tool earns its place in the context window through clear utility and minimal overlap, with robust metadata to guide agent decision-making.

Cross-Functional & Educational Domain Collaboration

Cross-Functional Collaboration: Partner with Product, Research, and Education teams to translate complex educational workflows into optimal context configurations, understanding which information signals matter most for different teaching scenarios.
Model & Platform Integration: Collaborate with ML researchers and platform engineers to co-design architectures that integrate memory modules, retrieval adapters, and human-in-the-loop correction systems.

Mentorship & Standards

Technical Mentorship: Guide engineers on context engineering patterns, teaching the shift from prompt-first thinking to holistic context management, token budget awareness, and dynamic information curation.

What We're Looking For

Deep Systems & AI Experience: 7+ years building distributed systems with at least 2+ years in staff/senior roles. Hands-on experience building LLM applications, agentic systems, or context-heavy AI workflows with clear understanding of transformer architectures and attention mechanisms.
Context Engineering Expertise: Demonstrated experience managing context windows, building dynamic retrieval mechanisms, or designing context compaction strategies. Understanding of when context becomes a liability vs. an asset.
Technical Stack: Strong coding skills in Python, TypeScript/Node.js. Experience with our stack (TypeScript, Node.js, PostgreSQL, NextJS, Supabase) or similar. Familiarity with LLM APIs (OpenAI, Anthropic, etc.) and their context management patterns.
Information Architecture: Understanding of information retrieval, structured data representation, and strategies for organizing knowledge for AI consumption.
Educational Context Awareness: 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.
Leadership & Impact: Track record of architecting information systems, making high-leverage architectural decisions, and mentoring engineers on sophisticated technical concepts.

Nice to Have

Experience with Model Context Protocol (MCP), context window optimization for specific model families, or building context-aware agent frameworks
Familiarity with educational technology platforms, curriculum databases, or EdTech content management
Background in semantic search or hybrid retrieval systems
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.

Context Engineering EdTech Jobs

Staff Context Engineer, AI Systems