Applied AI Prompt Engineer - DeVry University - Remote, OR

DeVry University strives to close our society’s opportunity gap and address emerging talent needs by preparing learners to thrive in careers shaped by continuous technological change. Through innovative programs, relevant partnerships, and exceptional care, we empower students to meaningfully improve their lives, communities, and workplaces.

Our colleague experience is an area of obsessive focus. At DeVry University, we care about you. Because, only through you can we deliver our unique Care Formula to our learners and partners.

Overview

The Applied AI Prompt Engineer designs, optimizes, and maintains the prompts, agent behaviors, context structures, and Retrieval-Augmented Generation (RAG) workflows that power DeVry’s enterprise AI ecosystem—including Copilot, ChatGPT, agentic workflows, and internal knowledge tools.

This is a hybrid role blending prompt engineering, operational AI lifecycle management, and cross-functional collaboration. You will rapidly prototype prompt variations, run evaluations, maintain knowledge pipelines, and ensure outputs remain accurate, compliant, and aligned with DeVry’s tone and policies.

The ideal candidate is fast, curious, experimental, and skilled at translating human-to-human support scenarios into reliable AI-driven interactions.

Key Responsibilities

Prompt Design & Optimization
• Design and maintain high-quality prompts, and agent instructions for enterprise AI platforms.
• Rapidly prototype and iterate prompt variants using structured experimentation, evaluation metrics, and A/B testing.
• Build evaluation rubrics, structured test cases, and prompt datasets to measure accuracy, tone, consistency, and policy alignment.
• Adapt prompts for higher-education use cases (e.g., advising, HR, faculty support, IT, student services) while maintaining institutional tone and compliance.

RAG & Knowledge Integration
• Curate and manage document ingestion, embeddings, and knowledge base updates to ensure relevant, current, and contex