MemU is an Agentic Memory Layer designed for AI agents and LLM-powered applications.We focus on solving hard problems around long-term memory, accurate retrieval, and controllable context, beyond traditional RAG systems.As a Backend Engineering Intern, you will work on real AI infrastructure, not demos or toy projects.Your code will directly ship to production systems and open-source repositories.
Develop and maintain core backend services of MemU:
- Memory CRUD, memory categories, memory historyMemory retrieval, ranking, and filtering
- Design and implement APIs for AI agents & LLM applications:Chat / Memorize / Response APIsToken usage and context control
- Work on data and storage layers:Vector databases, document stores, relational databasesMemory schema design and evolutionHelp solve engineering challenges:API reliability and performance
Concurrency, scalability, and cost efficiency
- Contribute to the open-source community:Fix issues, implement features, submit PRs
- Improve README, docs, and usage examplesCollaborate closely with product and agent designers to iterate on real use cases Requirements
Must Have:
- Currently enrolled student (any major; CS-related preferred)
- Solid backend fundamentals
- Proficient in at least one backend language (Python / Node.js / Go)
- Basic understanding of APIs, databases, and data structuresComfortable reading English technical documentation and writing basic technical messagesGenuine interest in AI, LLMs, agents, and developer tools
- Experience with vector databases (FAISS, Milvus, Weaviate, pgvector, etc.)Hands-on experience with RAG, agents, or LLM-based systems
- Open-source contributions (Issues / PRs)Strong curiosity about system design and AI infrastructure
What You’ll Gain
- Hands-on experience building real AI infrastructureDeep understanding of Agent memory, RAG, and LLM systems
- Public open-source contributions (GitHub-visible)
- Direct collaboration with a fast-moving startup teamOpportunity for long-term collaboration or full-time conversion
Kindly note that only shortlisted candidates will be notified.
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