AI Engineer, Internship – Intelligent Question Bank Platform

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: Apply tot his job Apply To this Job