AI Prompt Engineering | Learning Optimization | EdTech InnovationAt ibGuru, we are pioneering the future of AI-driven education, integrating cutting-edge AI models to enhance grading, feedback, and subject-specific tutoring. We are looking for an AI Learning Specialist who can prompt, fine-tune, and optimize our AI systems to deliver accurate, high-quality educational responses.
This is a hands-on role ideal for someone passionate about AI in education, skilled in AI prompting, and eager to improve automated learning experiences for students worldwide.
What You’ll Do
Fine-Tune AI Grading & Feedback•
Test and refine AI-generated grading to ensure accuracy and consistency.
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Adjust AI responses to match subject-specific mark schemes and IB-style grading.
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Identify and correct errors in AI feedback to align with real-world teacher grading standards.
Optimize Subject-Specific AI Chatbot Responses•
Ensure our AI tutors provide helpful, accurate, and contextual explanations for IB subjects.
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Improve AI conversational flow, ensuring explanations are clear and concise.
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Modify AI prompting strategies to refine chatbot performance.
Develop AI Prompting Strategies•
Craft and experiment with prompt engineering techniques to improve AI output quality.
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Continuously test and adjust AI models based on student interactions and feedback.
Collaborate with Content Editors & Developers•
Work closely with subject-specific content editors to validate AI accuracy.
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Provide insights to the AI development team on necessary improvements.
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Bridge the gap between educators and AI engineers to ensure educational quality.
Who We’re Looking For
Strong Understanding of AI & Prompt Engineering – Experience with AI-powered tools like ChatGPT, Claude, Gemini, or Llama. Analytical & Detail-Oriented – Ability to identify and correct AI-generated errors in grading and tutoring. Passionate About EdTech – Interested in AI-driven learning, educational psychology, and digital teaching methodologies. Problem-Solver – Able to experiment, iterate, and improve AI performance based on real-world student usage.