Ai Product Manager Intern

Role Overview

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 Responsibilities1) 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

2) AI Conversation Design & Evaluation

• 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

3) Experimentation & Execution

• 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

4) Prompt Engineering & LLM Optimization

• 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

5) Reporting & Stakeholder Communication

• Prepare clear, structured performance reports and presentations for management
• Translate data into actionable product recommendations
• Support weekly reviews and experiment readouts

Requirements

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)

Preferred SkillsData Analysis

• Data analytics experience with structured and/or unstructured (conversational) data analysis
• Tools: Python, SQL, R, PostHog, GA4, or similar analytics tools

AI Automation Exposure

• Exposure to no-code/low-code tools: Zapier, n8n, make.com or similar analytics tools
• Basic familiarity with APIs or data flows

Design & Communication

• Ability to create clear PowerPoint/Slides presentations
• Basic UX/UI understanding (user flows, wireframes)