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We are looking for an AI Product Manager Intern to support the design, analysis, and optimisation of AI-driven product experiences. You will work on LLM-powered features (e.g., conversational flows, automated follow-ups, internal copilots) and contribute to data-driven product decisions.
This role blends product thinking, analytics, and hands-on work with AI systems.
Key Responsibilities2) AI Conversation Design & Evaluation3) Experimentation & Execution4) Prompt Engineering & LLM Optimization5) Reporting & Stakeholder Communication
- Product Analytics & Performance
- Analyse product and user data to identify drop-offs, trends, and opportunities
- Define and track key metrics (activation, conversion, retention, task success)
- Build simple dashboards/reports to monitor product performance
- Design conversation flows for AI assistants (e.g., onboarding, support, follow-ups)
- Evaluate conversations using metrics such as response accuracy, resolution rate, and user engagement
- Iterate on flows based on observed user behaviour and edge cases
- Support A/B testing of AI flows, messaging, and product changes
- Document hypotheses, experiment design, and results
- Work with engineers/designers to implement and iterate quickly
- Develop and refine prompts for specific use cases (e.g., sales follow-ups, support responses)
- Implement guardrails (tone, scope control, fallback handling)
- Test prompt variations and document performance differences
- Prepare clear, structured performance reports and presentations for management
- Translate data into actionable product recommendations
- Support weekly reviews and experiment readouts
Required Skills
- AI / Product (Important)
- Basic understanding of LLMs and prompt design
- Familiarity with chatbot / conversational UX principles
- Ability to evaluate AI outputs critically (accuracy, tone, relevance)
- Proficiency in Excel / Google Sheets (pivot tables, basic transformations)
Data Analysis
- Data analytics experience with structured and/or unstructured (conversational) data analysis
- Tools: Python, SQL, R, PostHog, GA4, or similar analytics tools
- Exposure to no-code/low-code tools: Zapier, n8n, make.com or similar analytics tools
- Basic familiarity with APIs or data flows
- Ability to create clear PowerPoint/Slides presentations
- Basic UX/UI understanding (user flows, wireframes)
Key Skills
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