Product Head – AI & Computer Science Programs

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

• Masters (preferred) or Ph.D. in:
• Computer Science
• Artificial Intelligence
• Machine Learning
• Data Science
• Or related fields from a recognized university
• Bachelors 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 training

Experience Requirements

Total Experience Required: 58 years

• AI Technical Experience: 23 years
• ML model building
• Data pipelines
• Generative AI tools
• AI application development
• Curriculum development or academic leadership experience preferred.

Key Responsibilities

1. 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.