A
Not Specified Permanent

Fort Worth, Texas · USA job

AI Learning Architect

AMN Healthcare

Fort Worth, Texas

Job description

Overview

In this role you will design and build a next-gen AI-powered learning ecosystem for AMN Healthcare. You'll bridge instructional design with AI engineering to create adaptive, data-driven training across the organization. You work with subject matter experts, IT, and the Learning team to prototype scalable learning solutions. You'll own the architecture, implementation, and continuous improvement of AI-enabled training pathways. This is a hands-on builder role shaping corporate learning for the coming years.

Responsibilities
  • Directly build, configure, and maintain AI-powered learning modules and automated assessment tools
  • Design and implement AI applications using prompt engineering and low-code/no-code automation
  • Structure data and content into modular, adaptive learning pathways
  • Evaluate, test, and integrate modern generative AI design tools with LMS/LEP platforms
  • Set up tracking with xAPI or standard learning metrics and use data to improve outcomes
  • Debug prompt configurations, manage content databases, and ensure accuracy over time
  • Incorporate data privacy, disclosure, human review, accessibility, and bias checks in collaboration with IT, Legal, and Compliance
  • Document architectures and coach designers to ensure maintainability
Key requirements
  • 3-5+ years in instructional design, educational tech, or similar tech-adjacent roles with AI integration portfolio
  • Proficiency with modern generative AI models, prompt workflows, and low-code automation or APIs
  • Grounding in adult learning theories (ADDIE, SAM, cognitive load) applied to digital interfaces
  • Ability to translate technical behavior into intuitive user experiences and explain AI to non-technical audiences
  • Working knowledge of learning platforms and data standards like xAPI or SCORM
  • clear communication
  • problem-solving
  • collaboration
  • generative AI models
  • prompt engineering
  • RAG (retrieval-augmented generation)

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