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

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