AI Engineer, Internship – Intelligent Question Bank Platform

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Job Description:

  • Work closely with the founder to design and build an AI-powered content generation system from the ground up
  • Contribute to meaningful parts of the product end-to-end from how the system ingests and understands source material, to how it produces and validates outputs, to how instructors interact with and review what the system generates
  • Build and iterate on LLM-driven pipelines
  • Work with retrieval and embedding techniques to ground outputs in real source material
  • Develop backend services and APIs that tie everything together
  • Think about output quality and building evaluation steps, catching failure modes, and improving the system based on real instructor feedback
  • Research new tools and techniques as the AI space evolves and bring relevant ideas directly into the product
  • This is a generalist role at an early-stage product where you'll wear multiple hats, work with ambiguity, and have direct input into how things are built.

Requirements:

  • Strong foundation in software engineering: data structures, APIs, system design
  • Proficiency in Python (primary language for AI/ML pipeline work)
  • Experience with REST APIs and at least one database (PostgreSQL preferred)
  • Ability to work independently, ask sharp questions, and iterate fast
  • Strong debugging and problem-solving instincts
  • Demonstrated side projects or shipped code (GitHub portfolio required)
  • Genuine interest in AI systems and education technology
  • Direct experience with LLM APIs: OpenAI, Anthropic Claude, or Google Gemini
  • Hands-on experience with RAG systems: embedding models, vector databases (Pinecone, Weaviate, pgvector, Chroma)
  • Familiarity with prompt engineering techniques: few-shot prompting, chain-of-thought, structured JSON outputs
  • Experience with NLP pipelines: text chunking, tokenization, semantic search
  • Knowledge of LaTeX syntax and math rendering libraries (MathJax, KaTeX)
  • Experience with image generation APIs or SVG programmatic generation
  • Familiarity with AI evaluation frameworks or automated test harnesses for LLM outputs
  • Cloud platform experience: AWS, GCP, or Vercel for deployment
  • Experience with job queues: Celery, Bull, or similar
  • Exposure to educational content standards or psychometrics is a bonus

Benefits:

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