Job Title

The Product Head – AI & Emerging Technologies will be responsible for designing, developing, and leading an advanced AI-based academic program (Kids-to-Masters level). The role demands strong technical expertise in AI/ML, deep academic knowledge, and hands-on experience in instructional design. The candidate should blend academic leadership with modern AI skills to drive an innovative, future-focused curriculum.The ideal candidate will collaborate with academic and marketing teams, create structured learning pathways, ensure high-quality content delivery, and guide instructors and learners across different levels of expertise.Essential Academic Qualifications- Master’s (preferred) or Ph.D. in: - Computer Science - Artificial Intelligence - Machine Learning - Data Science - Or related fields from a recognized university - Bachelor’s degree in Engineering/Mathematics with strong AI/ML certifications may also be accepted with proven experience.Technical & Pedagogical Certifications- AI/ML practitioner certifications such as: - TensorFlow Developer - AWS Machine Learning - Google AI, Coursera Deep Learning, IISc Agentic AI - Pedagogical/teaching certifications like: - B.Ed / M.Ed - Instructional Design Certification - UNESCO AI competency or similar frameworks trainingExperience RequirementsTotal Experience Required: 5–8 years- AI Technical Experience: 2–3 years - ML model building - Data pipelines - Generative AI tools - AI application development - Curriculum development or academic leadership experience preferred.Key Responsibilities1. Program Development & Leadership- Design and develop a structured AI and Data Science curriculum from foundational to advanced levels. - Lead academic planning, course mapping, and learning outcomes based on global AI learning frameworks. - Create learning pathways suitable for school students, graduates, and professionals.2. Technical Content Creation- Develop high-quality learning modules, assessments, labs, and AI-based project content. - Ensure curriculum includes modern AI tools, ML workflows, data pipelines, and generative AI applications.3. Instructional & Pedagogical Excellence- Apply instructional design principles for engaging learning content. - Train faculty members on content delivery, teaching methods, and student engagement. - Maintain academic rigor and ensure excellence in teaching-learning practices.4. Hands-On AI/ML Projects- Guide learners in building AI/ML models and real-world use-case projects. - Ensure integration of modern AI tools, frameworks, and practical code implementation.5. Program Quality Assurance- Conduct regular curriculum reviews to keep course content aligned with industry standards. - Evaluate student performance and continuously enhance teaching methodologies.6. Collaboration & Stakeholder Management- Coordinate with academic heads, curriculum designers, and technical experts. - Participate in strategic planning for program expansion and new course development. - Drive B2B partnership with Schools, Colleges for CoE (Centre of Excellence) integration, Pilots and Govt. scheme alignment (NIDHI, DST, CSR) - Set KPIs: enrolment growth, student outcomes (Skills, Placements), ROI attribution and NAAC / CoE accreditation readiness.