Instructional Designer $200,000 USD/year Pay is set based on global value, not the local market.
Most roles = hourly rate x 40 hrs x 50 weeks
Description
This role is designed for academic leaders who prefer designing systems to critiquing them. You bring fluency in your discipline sufficient to recognize high-quality learning, the rigor to translate that insight into rubrics and AI-driven quality mechanisms, and the pragmatism to respond quickly to imperfect data. Student improvement matters to you, and you are willing to be evaluated by that measure.
2 Hour Learning pursues an objective the broader software and education sectors seldom undertake. Teachers, textbooks, and traditional instructional scaffolding are absent from the product. AI serves as the operational foundation. In this capacity, you will deploy it to produce and refine learning materials, architect interventions, oversee quality standards, and advance platform capabilities. The tempo resembles high-output environments in technology, consulting, or finance more than typical educational settings, and the reward is direct accountability for student outcomes in your subject across multiple campuses.
This position centers on operational leadership. You will develop AI-enabled enhancements to the learning ecosystem, act on student performance indicators through focused interventions, produce evidence-backed decision documentation, and lead a team measured against explicit benchmarks tied to MAP, AP, SAT, and ISEE performance. You will also collaborate closely with product, engineering, and data science to identify platform priorities. This role suits someone who prioritizes AI by default, conducts independent analysis, delivers under uncertainty, and accepts full ownership of results. It will not suit those who favor consensus-driven timelines, minimal accountability, or reliance on established methods.
You will occupy a central leadership position within the academics team, wielding meaningful influence over subject performance and the evolution of the broader learning infrastructure. Your colleagues will depend on your standards, your discernment, and your capacity to translate student data into strategic action. If that prospect feels motivating rather than daunting, this role is likely suited to you.
What you will be doing
- Learning Ecosystem Enhancements — AI-driven refinements to K–12 subject-specific learning experiences, including content, adaptive pathways, and student interventions, guided by student feedback, analytics, assessment results, and coaching observations.
- Data-Driven Academic Interventions — Focused intervention strategies for students or cohorts not meeting progress expectations, informed by MAP, AP, SAT, ISEE, and comparable performance metrics.
- Student Performance Decision Records — Documented, evidence-based decisions that capture actions taken to improve student performance, supported by dashboards, analytics, ticketing systems, surveys, coaching interactions, and assessment data.
- Learning Ecosystem Improvement Specs — Actionable specifications for enhancements to be executed by product, engineering, and data science teams, including problem framing, supporting evidence, anticipated student impact, and acceptance criteria.
What you will NOT be doing
- Wrapping traditional education models in AI packaging. This is not about digitizing classroom instruction – we are rebuilding learning architecture from first principles.
- Conducting analysis in a vacuum. You will regularly interact with K-12 students, treating their feedback as critical input from the customers we serve.
- Waiting for widespread agreement before taking action. You will advocate for an ambitious vision and mobilize stakeholders around outcomes grounded in data.
- Defaulting to established practices. You will have latitude to test novel strategies for motivation, assessment, and instruction.
- Treating AI as a risk to education. In this environment, you will leverage AI as a powerful instrument to transform learning, not as a challenge to be managed.
Key responsibilities
Lead the advancement of AI-powered, teacher-independent education to achieve outstanding student outcomes across multiple campuses. Combine rigorous data analysis with consistent student engagement to iteratively enhance our learning ecosystem, with success measured by AP exam results and MAP assessment growth.
Candidate requirements
- Master's degree or higher in Educational Science, Learning Science, Psychology, Psychometrics, Instructional Design, or a related field
- At least 5 years of experience in academic or EdTech leadership roles, with direct people management responsibility (hiring, performance evaluation, coaching, termination decisions)
- Demonstrated experience using AI tools as part of day-to-day professional workflows, and willingness to rely on AI extensively to improve academic and operational outcomes.
- Strong understanding of learning science principles, such as Cognitive Load Theory and Mayer's Multimedia Principles, and data-driven educational approaches
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