Instructional design and product QA intern

Cynuria is supporting our sister company, an AI-driven startup bridging the gap between complex instructional theory and engaging, dynamic learning experiences. We are looking for a Graduate Intern in an Instructional Design, EdTech, or Learning Sciences program (currently enrolled or recently completed). You will help our product team research, test, and validate our platform’s AI outputs, supporting alignment of instructional materials with established learning theories and helping to identify and document gaps in quality and the instructional designer user experience.
Description

Job title: Instructional Design and Product QA internEmployment type: Internship, W2, Authorized to work in the United States requiredJob location: Remote, no travelWeekly hours: Up to 30 hours/wk (Cynuria core hours: 9:00 am - 5:00 pm EST)Compensation: Unpaid (4/20/2026 - 7/31/2026) This role offers the potential to transition into a paid position for those who consistently meet or exceed performance.What you’ll do:Instructional design auditingAudit AI outputs against established frameworks such as Bloom’s Taxonomy and Gagné’s Nine Events of Instruction.Evaluate the instructional content generated, check for a logical, scaffolded learning structure that makes sense for a human learner. QA testing Systematically test the platform functionality to identify UI/UX friction points for instructional design end users.Identify "pedagogical bugs": instances where the AI provides instructionally unsound advice or skips critical training steps. Then document these for the product and technical team.Prompt engineering support Work with the Product Manager to test and tweak the system prompts that guide the AI, helping to improve the "voice" and instructional quality of the assets generated in the platform. Research and data validationIdentify and curate high-quality, validated datasets and documentation to inform the AI’s backend: sourcing peer-reviewed content and Open Educational Resources (OER).Cross-reference and validate AI-generated content against authoritative sources to check for factual accuracy and prevent "hallucinations" in high-stakes training topics.Reference management: contribute to organizing a centralized library of sources that the AI can use to cite its work, helping end users trust every asset generated.Who you are:Current or recent graduate student: enrolled in or have completed a graduate program related to Instructional Design, Educational Technology, or Learning Science.Framework fluent: You don't just know what ADDIE is; you know how to apply it.Tech-savvy: You are experienced with (or are willing to learn) bug-tracking and project management software.Skilled researcher: You can navigate databases (e.g., Google Scholar) and distinguish between "popular content" and "validated data."AI literate: You have practical experience with LLMs (ChatGPT, Claude, Gemini) and a strong interest in how AI can be applied to instructional content design and development. Work environment and physical demands of the job: Working remotely, all work is computer-based, including frequent video meetings. Core working hours on Eastern Standard Time.



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