Artificial Intelligence Trainer

Role & responsibilities

A. Student Training & Facilitation

• Conduct engaging, hands-on AI sessions for students of Grades 6-12 and adapt facilitation to different age groups and prior skill levels.
• Explain complex AI, coding, product and digital-creation concepts using simple, age-appropriate examples, demonstrations and project-based activities.
• Guide students through ideation, prototyping, building, testing, debugging, peer feedback, iteration and presentation of AI-enabled projects.
• Provide greater scaffolding to younger learners while encouraging senior students to work with higher independence, testing depth, documentation and justification.
• Maintain a safe, inclusive and participative learning environment and provide constructive, actionable feedback on student work.

B. Curriculum & Learning Journey Development

• Design and develop AI curricula, modules and learning journeys for schools, educational institutions and other organisations based on learner profile, prior knowledge and desired outcomes.
• Translate programme outcomes into structured learning sequences covering objectives, instructor preparation, materials, Responsible AI, Hook/Core/Wrap activities, student outputs, peer testing, reflection, assessment, troubleshooting and differentiation.
• Develop lesson plans, facilitator guides, student worksheets, project briefs, prompt templates, activity sheets, assessment instruments, rubrics and capstone/project-showcase frameworks.
• Define skill progression, prerequisite knowledge, project milestones and observable evidence of learning across beginner, intermediate and advanced learner groups.
• Continuously improve curricula using learner performance, facilitator feedback, tool changes and programme requirements.

C. Technical Mentoring & Project Development

• Mentor students in no-code app development, AI-assisted game development, AI-agent design, prompt engineering, digital content creation and product thinking.
• Support learners in understanding data structure, user experience, basic databases, HTML/CSS/JavaScript logic, integrations, testing and responsible use of AI-generated code/content.
• Prepare demonstrations, starter files, sample projects and troubleshooting guidance before sessions; test tools and workflows in advance.
• Help students present projects professionally and explain their design choices, AI contribution, limitations, safety controls and next-step improvements.

D. Responsible AI, Assessment & Quality

• Embed privacy, consent, copyright, attribution, bias awareness, fact-checking, hallucination management, transparency, human review and responsible publication into teaching and curriculum.
• Assess observable evidence including understanding, prompt quality, creativity, accuracy, functionality, testing, responsible AI, collaboration, presentation and reflection.
• Document learner progress, session observations, recurring technical issues and curriculum improvement recommendations as required by the programme team.
• Coordinate with programme, curriculum and school stakeholders on session readiness, student support, project showcases and delivery quality.

Preferred candidate profile

Strong understanding of Generative AI, large language models, prompt engineering and safe human-AI collaboration.

• Working knowledge of no-code/low-code app development, basic data modelling, forms, database mapping and user experience principles.
• Working knowledge of HTML, CSS and JavaScript sufficient to create, explain, test and debug beginner-to-intermediate browser-based projects.
• Understanding of AI agents, conversational flows, instructions, knowledge sources, guardrails, testing and basic tool/integration concepts such as webhooks.
• Understanding of creative-AI workflows for visual identity, branding, marketing content, presentations, audio/video and campaign development.
• Knowledge of curriculum design, instructional design, project-based learning, age-appropriate pedagogy, differentiation and rubric-based assessment.
• Strong grounding in Responsible AI, privacy, digital safety, copyright/attribution, bias, fact-checking, hallucinations and human review.

Skills - Technical & Instructional

• Generative AI / LLM tools: hands-on proficiency with ChatGPT, Google Gemini, Claude, Microsoft Copilot or comparable LLM platforms.
• No-code / low-code app development: working knowledge of Glide; exposure to comparable platforms such as Bubble, AppSheet, Softr, Adalo or equivalent is desirable.
• Data and app back-end basics: Google Sheets and/or comparable structured-data tools such as Airtable; ability to explain rows, fields, categories, forms and data connections.
• Web and game development: HTML, CSS and JavaScript; familiarity with editors/environments such as VS Code, Replit, CodePen or similar, plus browser-based testing/debugging using Chrome or equivalent.
• AI-agent platforms: working knowledge of Botpress Studio; exposure to comparable platforms such as Voiceflow, Dialogflow, Microsoft Copilot Studio, Langflow or equivalent is desirable. Familiarity with knowledge bases, integrations and webhook concepts is an advantage.
• Creative and brand tools: familiarity with Adobe Express, Adobe Firefly, Illustrator, Fresco, Character Animator, Adobe Podcast and/or comparable design, video, audio and content-creation tools such as Canva or Figma.
• Productivity/collaboration: Google Workspace (Docs, Sheets, Slides, Drive) or equivalent productivity suites.
• Version control and project hygiene: familiarity with backup/versioning practices; Git/GitHub or similar version-control exposure is desirable.
• Ability to rapidly evaluate and learn emerging AI tools and determine their educational suitability, safety, accessibility and relevance to learning outcomes.
• Strong curriculum writing, instructional documentation, presentation, facilitation and assessment-design skills.

Competencies -

• Excellent verbal and written communication with the ability to simplify technical concepts for school learners.
• Strong classroom presence, patience, empathy and the ability to sustain student engagement through hands-on learning.
• Curriculum and learning-experience design mindset with strong sequencing, scaffolding and differentiation skills.
• Problem-solving, debugging and structured experimentation; ability to model productive responses to failure and iteration.
• Creativity, curiosity and willingness to continuously learn as AI tools and practices evolve.
• High ownership, preparation discipline and attention to learner safety, quality and documentation.
• Ability to collaborate effectively with school leaders, teachers, programme teams and curriculum stakeholders.