🪃 About Memorang

Our mission is to automate how humans acquire and master skills. The first step in our journey is to build the AI stack for education to transform the credentialing and publishing industries with the best tools to build curricula, assessments, and apps at scale.

After winning #1 (of 1,500) in the Vercel AI Accelerator we bootstrapped to millions in revenue and profitability while delivering over 200MM assessments via our AI platform. We also just closed our first strategic investment to scale faster and deploy our solution to millions of additional learners.

We're a lean, talented team that rewards agency, curiosity, and shipping real products that directly impact the lives of millions.

"Memorang has literally the best gen AI results I've seen applied to a real world problem."

• Director of Trust and Safety, Google Deepmind

🎯 Role

As a Product Engineer, you'll own problems end to end, from architecture to production. You'll work alongside a team that moves fast, adapts quickly, and builds solutions that unlock million-dollar product lines. You'll be at the forefront of applied AI in education, designing the systems, data models, and APIs that deliver transformative learning experiences to millions of users worldwide.

🛠️ Sample projects could include…

• Building a new AI-powered assessment mode that generates personalized practice questions, from prototype to production in 2 weeks.
• Simplifying partner app configuration by creating a responsive admin dashboard in Next.js that eliminates the need for engineering support.
• Designing a graph-based content recommendation engine using Neo4j that increases learner engagement by 25%.
• Modeling the relational schema for a new content pipeline, balancing normalization against real read patterns to keep queries fast across millions of rows.
• Architecting an event-driven ingestion service and drawing the right datastore boundaries between relational and graph systems.
• Improving API response times by optimizing database queries and caching strategies with Redis, reducing latency from 800ms to 120ms.
• Driving adoption of reusable patterns by refactoring a legacy feature into a component library that enables 3 other teams to ship faster.
• Partnering with the Platform team to implement a serverless API using AWS Lambda and LangGraph that processes 10M+ assessment submissions monthly.

🤝 You might be a fit if you…

• Can teach a course on system architecture, schema design, relational and graph data modeling, query performance, and event-driven systems.
• Have deep expertise in modern frontend development using React, performance tuning, and UI state management.
• Apply design patterns and software engineering principles to real-world problems.
• Have shipped LLM-powered features in production.
• Design systems that balance velocity with extensibility.
• Are passionate about solving complex technical problems and ship production-ready code quickly.
• Excel at written communication and async collaboration.