Backend Engineer - Node.js / AI Infrastructure

About the Role

This Backend Engineer role involves building the AI infrastructure for a cutting-edge interactive audio platform, focusing on scalable backend services, vector search, and hybrid search at scale.

You will be responsible for designing and implementing production-grade RAG pipelines, chunking strategies, embedding generation, retrieval logic, and context assembly, as well as API design for moderation workflows, content classification, and AI-assisted review queues.

Key Responsibilities

• Design and implement production-grade RAG pipelines, including chunking strategies, embedding generation, retrieval logic, and context assembly.
• Develop scalable backend services using Node.js and Express, integrating with MongoDB for efficient data storage and retrieval.
• Implement vector search and hybrid search at scale, ensuring high retrieval quality and performance.
• Design and implement background job infrastructure using BullMQ for async ingestion and processing.
• Develop API design for moderation workflows, content classification, and AI-assisted review queues.
• Debug and optimize RAG pipelines, vector search, and hybrid search to improve retrieval quality and performance.

Skills & Qualifications

• Strong understanding of RAG pipelines, including chunking strategies, embedding generation, retrieval logic, and context assembly.
• Proficiency in Node.js, Express, and MongoDB for building scalable backend services.
• Experience with vector search and hybrid search at scale, including sparse retrieval methods and dense vector search.
• Bachelor's or Master's degree in Computer Science or related field.
• Good understanding of API design principles and software development best practices.
• Experience with BullMQ for async ingestion and processing is a plus.

What You'll Learn

In this role, you will gain hands-on experience with building AI infrastructure for a real-world application, including designing and implementing scalable backend services, vector search, and hybrid search at scale.

You will also learn about RAG pipelines, chunking strategies, embedding generation, retrieval logic, and context assembly, as well as API design for moderation workflows, content classification, and AI-assisted review queues.

Resume Tip

When applying for this role, make sure to highlight your experience with RAG pipelines, vector search, and hybrid search, as well as your proficiency in Node.js, Express, and MongoDB.

Include specific examples of your work, such as projects or code snippets, that demonstrate your skills in building scalable backend services and AI infrastructure.