AI Learning Strategist:

Primary Skills: Learning Science & Pedagogy (Expert), AI-Native Learning Design (Expert), Educational Technology - EdTech (Expert), Learning Efficacy Metrics (Advanced), Adaptive Learning Systems (Advanced), Stakeholder Collaboration (Advanced)
Location: REMOTE
Contract : W2
Duration: 12 months
Pay Range: $50 - $55 Per Hour
#LP

JOB SUMMARY:
Client is seeking an AI Learning Strategist to define the AI-native learning experience by translating learning science into practical frameworks and methodologies. This role partners with the Innovation Program Manager to ensure that AI innovations are grounded in evidence-based pedagogy rather than just operational efficiency. You will pioneer methodologies that enable personalized, outcome-driven learning at an enterprise scale, shaping how the organization builds AI-native capabilities.

JOB REQUIREMENTS:
Define practical AI-native learning methodologies and design principles for instructional designers.
Partner with the Innovation PM to design and test pedagogical hypotheses in AI pilots.
Create documentation, templates, and "exemplar experiences" that demonstrate AI-native principles.
Define quality criteria and learning efficacy metrics for diverse AI-enabled learning formats.
Analyze learner performance data to bridge gaps between technical capabilities and learning outcomes.
Build internal design capabilities through workshops, coaching, and embedded learning science expertise.
Track emerging AI learning models and research to refine the broader ServiceNow learning strategy.
Communicate the business and quality impact of adopting AI-native methodologies.

Must-Have Skills:
Instructional Design Foundation: 5-7 years of experience in ID or LXD with a deep mastery of learning science application.
Hands-on AI-Enabled Learning: Proven experience with adaptive learning systems, intelligent tutoring, personalized learning paths, or AI-assisted assessments.
Systems Thinking: Ability to connect the dots between learning science, AI technical capabilities, operational constraints, and business outcomes.
Framework Development: Experience creating learning methodologies or standards that were successfully adopted by other designers in an enterprise environment.
Scientific Experimentation: Ability to design rigorous tests for learning hypotheses, focusing on efficacy metrics rather than just user experience.

Industry Experience:
Strong background in Enterprise Learning, EdTech, or Digital Learning environments.
Experience working cross-functionally with Product, Innovation, and Curriculum Development teams.

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