Job Description
This role is responsible for designing, testing, and optimizing prompts for Large Language Models (LLMs) to produce high-quality, reliable outputs across a range of mission use cases - translating complex requirements into effective AI interactions, within an Agile delivery environment.

Responsibilities
• Prompt Design & Optimization - Develop, refine, and iterate on prompts for generative AI models (LLMs) to elicit desired behaviors and outputs.
• Iterative Testing & Analysis - Conduct structured testing to compare prompt variations and drive continuous improvement.
• Collaboration - Work closely with cross-functional teams to integrate prompts that streamline manual processes.
• Fine-Tuning & RAG Support - Provide input on model fine-tuning and Retrieval-Augmented Generation (RAG) strategies.
• Problem Solving - Debug unexpected model behaviors, identifying root causes in prompt structure or data context.

Required Qualifications
• Must be a U.S. Citizen with the ability to pass a federal background investigation (criminal, drug use, and misconduct checks).
• Bachelor's degree in Computer Science, Software Engineering, IT, or related field (equivalent experience considered)
• 0-3 years of professional software development experience or relevant academic project work
• 1+ year of hands-on experience with LLMs (e.g., OpenAI GPT series, Llama, Gemini)
• Proficiency in at least one programming language (Python, JavaScript/TypeScript)
• Familiarity with prompt engineering techniques (few-shot, chain-of-thought, structured outputs, function calling)

Desired Qualifications
• Strong, data-driven problem-solving skills
• Strong written and verbal communication skills
• Exposure to RAG concepts, embeddings, and vector databases
• Understanding of AI safety considerations (prompt injection, bias, data privacy)
• Exposure to Agile/Scrum environments