AI Foundation Trainers

• Position: AI Foundation Trainers (2 open positions)
• Duty Station: Field-based, with assignments at partner colleges and universities across Nepal; base at NAAMII, Kupondole
• Employment Type: Consultancy engagement — full-time level of effort during active curriculum development and delivery periods
• Reports to: Project Manager; day-to-day coordination with the Community Manager

Application Deadline: August 30, 2026

Position Summary

NAAMII is calling for AI Foundation Trainers who will skill the current workforce to transform their existing organizations to AI native organizations. The trainers will contribute to curriculum design, practical delivery and continuous improvement of a learning pathway that enables learners to understand core AI concepts, work with data and code, build responsible AI-enabled solutions, and progress towards deeper technical study or applied roles.

Key Responsibilities

• Shape the AI Foundation Learning Experience
• Contribute to the design, review and continuous improvement of the AI Foundation curriculum, modules, practical exercises, assessments and trainer resources.
• Translate core concepts in programming, data, machine learning and responsible AI into clear, structured and engaging learning experiences.
• Use learner performance, institutional feedback and emerging technical developments to keep the pathway relevant and rigorous.
• Redesign Technical Learning Through Practice
• Move learning beyond lectures towards hands‑on coding, experimentation, collaborative problem solving and project-based learning.
• Help learners connect technical concepts with real challenges from education, research, institutions, communities and industry.
• Create a learning environment where learners can test ideas, debug, reflect, ask questions and build confidence through practice.
• Facilitate Applied and Responsible AI Development
• Guide learners in using standard programming, data and AI tools to explore datasets, build basic models, evaluate outputs and develop practical prototypes.
• Help learners understand model limitations, data quality, bias, privacy, ethics and responsible development practices.
• Adapt examples and projects to different academic disciplines while maintaining the technical quality and intended learning outcomes of the AI Foundation framework.
• Build Learner Capability and Progression
• Support learners with varied levels of mathematics, programming and prior exposure to AI through structured guidance and differentiated support.
• Guide learners through practical activities, assignments, assessments and projects using Tangible, approved coding environments and other learning tools.
• Help learners build the confidence and foundation needed to apply AI in their discipline, pursue advanced learning, or progress towards AI‑enabled roles.
• Strengthen the AI Foundation Model
• Capture learner feedback, common misconceptions, technical barriers, successful projects and emerging learning needs from each cohort.
• Document evidence of learner participation, technical progression, project completion and practical application, together with required attendance and assessment records.
• Work with NAAMII curriculum, research, programme and institutional teams to improve the content, pedagogy, delivery model and transition between AI Native, AI Foundation and AI Deep learning pathways.
• GESI, Accessibility and Safeguarding
• Create an inclusive, respectful and gender‑responsive technical learning environment in which women, marginalized groups and learners with different levels of prior access can participate confidently.
• Adapt facilitation, examples, pacing and learner support to reduce barriers related to language, disability, digital access, technical confidence and previous educational opportunity.
• Promote safe and responsible participation, protect learner wellbeing and privacy, and follow NAAMII and UDAAN safeguarding, GESI and ethical AI standards throughout design, delivery and assessment.

Required Qualifications

• Bachelor's or Master's degree in computer science, artificial intelligence, data science, software engineering, mathematics, statistics, education technology, or a closely related field.
• Strong understanding of programming fundamentals, data handling, machine learning concepts and responsible AI, with the ability to explain them clearly to learners.
• At least 2 years of experience in teaching, technical training, curriculum development, mentoring, software or data science or AI-related project work.
• Practical proficiency in Python and commonly used data science or machine learning tools and environments.
• Strong facilitation and communication skills; fluency in Nepali and working proficienc