AI Product Manager & Builder Intern

Be part of something BIG!

We are looking for an AI Product Manager & Builder Intern who can help turn ambiguous AI opportunities into practical, business-ready AI products. This intern will support the innovation AI initiative by combining product thinking, hands-on AI prototyping, business framing, and strong communication.

The intern will work closely with forward deployed engineers to translate business problems into clear requirements, user journeys, acceptance criteria, prototype priorities, and feedback loops. The role is intentionally positioned at the intersection of engineering and business: understanding what is technically possible, shaping it into a useful product direction, and explaining the value clearly to stakeholders.

We are looking for someone who is not only AI-curious, but a credible AI builder in the community. The ideal candidate should have visible evidence of building with AI, such as shipped prototypes, public demos, hackathon work, open-source contributions, technical content, community talks, or a strong portfolio of AI builds.

How You will Make An Impact:

• Support product management for the innovation AI initiative, including roadmap development, feature prioritisation, user journey mapping, success metrics, and end-to-end delivery coordination.

• Work closely with developer engineers to translate business problems into clear product requirements, user stories, acceptance criteria, workflow logic, edge cases, and prototype iteration priorities.

• Drive rapid prototyping using modern AI tools, LLMs, agentic workflows, no-code or low-code platforms, and AI-assisted development approaches to test new AI concepts aligned to enterprise needs.

• Shape the business angle of AI product work by assessing user value, operational impact, adoption barriers, stakeholder readiness, productivity gains, and value realisation potential.

• Conduct market and community scanning on emerging AI, GenAI, agentic AI tools, AI-assisted development patterns, and builder practices to identify opportunities for strategic adoption.

• Collaborate with AI engineers, solution teams, product owners, and business stakeholders to refine prototypes into scalable, secure, usable, and production-ready solutions.

• Prepare product briefs, demo scripts, stakeholder decks, leadership updates, recommendations, and strategic materials that communicate AI product value clearly in business terms.

• Develop frameworks and trackers for adoption planning, change management, user feedback loops, performance monitoring, and value realisation for AI products.

• Monitor product performance metrics, usage trends, user feedback, and adoption signals to inform iterative improvements and roadmap evolution.

• Promote AI-first ways of working by supporting communications, internal demos, training materials, onboarding activities, and knowledge-sharing sessions for AI products.

Skills for Success:

• Pursuing a Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, Business, Product Management, Design, Entrepreneurship, or a related field.

• Experience building AI prototypes, demos, automation workflows, product concepts, or AI-enabled tools. Demonstrated ability to work across technical and business stakeholders.

• Understanding of AI/GenAI concepts and enterprise applications.

• Hands-on use of AI tools, LLMs, agentic workflows, and AI-assisted development tools.

• Ability to define product requirements, user stories, acceptance criteria, and prototype test plans.

• Strong research, synthesis, and product documentation skills.

• Ability to evaluate AI ideas by feasibility, user value, adoption, and business impact.

• Very strong communicator able to explain technical ideas simply to both engineers and non-technical stakeholders.

• Strong critical thinking, structured problem-solving, and business storytelling.

• Comfortable working in ambiguity with a proactive, experimentation-driven mindset.

• Credible AI-builder presence, with the confidence to share demos, lessons, and community practices.

• Knowledge of digital collaboration tools, enterprise workflow systems, AI adoption practices, responsible AI considerations, and emerging AI workplace technologies.