01· 2026

NASA: AI Engineering

A vetted prompt-engineering DB + RAG pipelines for the Astrophysics Division.

AI Engineering Intern
overview

Inside NASA's Astrophysics Division I built internal AI tooling to make scientists faster and more consistent, turning scattered prompt knowledge into a single trusted system and making dense documents instantly queryable.

project image

The goals

  • ✦Centralize fragmented prompt knowledge into one trusted source
  • ✦Make large technical document sets searchable in seconds
  • ✦Raise the quality + consistency of AI-assisted work across the team

What I did

  • ✓Designed and shipped a Prompt Engineering database of 100+ vetted, reusable templates spanning policy summarization, document drafting, data analysis, and panel review workflows
  • ✓Built RAG pipelines for AI-assisted document querying across division archives, enabling mission-critical document intelligence
  • ✓Standardized prompting practices so outputs stayed accurate and repeatable across the team

Tools & skills

PythonRAGLLMsPrompt EngineeringVector Search

The results

→100+ vetted prompt templates in active internal use
→Document lookup time cut from hours to seconds
→A reusable RAG foundation other teams can build on
image
image
image
← Back to all work