Software Developer at Spider

You will transform an early-stage "vibe coded" prototype into a production-ready AI study platform. By architecting a sophisticated RAG pipeline and refactoring the existing Next.js/Supabase codebase, you will help university students connect fragmented course materials into a cohesive, searchable knowledge graph that powers accurate, context-aware AI learning assistance.

• Architect and optimize the RAG pipeline, including chunking strategies, embedding storage in vector databases, and retrieval logic for course materials.
• Refactor and clean the existing Next.js and Supabase codebase to improve maintainability, stability, and performance for real-world student testing.
• Implement core product features and modern UI components from Figma designs to create a polished, credible experience for university students.

• Proven experience with RAG architectures, vector databases (like pgvector or Pinecone), and optimizing LLM retrieval workflows for accuracy.
• Proficient in the full-stack TypeScript ecosystem, specifically building and deploying scalable applications using React, Next.js, and Supabase/Postgres.
• Pragmatic builder who excels at inheriting messy, early-stage code and making decisive trade-offs between speed and engineering excellence to ship MVPs.

• Direct technical ownership to architect a RAG pipeline from near-zero, moving beyond simple chatbot wrappers to create a genuine knowledge graph for education.
• High-impact opportunity to lead the technical transition from a working prototype to a stable MVP ready for upcoming university pilots.
• Total autonomy with a direct line to the founder, offering a fast-paced environment without micromanagement and a potential path to technical leadership.