AI-Driven E-Commerce Product Ownership
Budget: €6 – €12 EUR
I’m looking for a technical Product Owner who can weave modern AI capabilities into our day-to-day product requirements analysis for an e-commerce platform that is scaling quickly. The core of the assignment is to use AI tools—think ChatGPT, Claude, Jira-native ML, or your preferred stack—to mine customer feedback, transaction data, and stakeholder notes so that requirements emerge faster, cleaner, and with measurable rationale behind every backlog item.
Here’s what I need from you:
• A continuously updated product-requirements document that is generated (or at least heavily assisted) by AI and clearly maps features to business goals and user value.
• An AI-supported backlog in Jira or Azure DevOps that stays groomed two sprints ahead, complete with refined epics, user stories, and acceptance criteria.
• Dashboards or lightweight reports showing how the AI arrived at key insights, so the team can trust and iterate on them.
• A hand-off guide that documents the workflow and prompts used, making the process reproducible for internal staff.
Acceptance will be based on:
1. Clarity and traceability of requirements from data source to user story.
2. Demonstrated reduction in manual analysis time (baseline will be set during kickoff).
3. A backlog that engineering can pick up immediately without additional clarification.
If you thrive at the intersection of product strategy, AI tooling, and fast-moving e-commerce, let’s talk about timelines and next steps.
Here’s what I need from you:
• A continuously updated product-requirements document that is generated (or at least heavily assisted) by AI and clearly maps features to business goals and user value.
• An AI-supported backlog in Jira or Azure DevOps that stays groomed two sprints ahead, complete with refined epics, user stories, and acceptance criteria.
• Dashboards or lightweight reports showing how the AI arrived at key insights, so the team can trust and iterate on them.
• A hand-off guide that documents the workflow and prompts used, making the process reproducible for internal staff.
Acceptance will be based on:
1. Clarity and traceability of requirements from data source to user story.
2. Demonstrated reduction in manual analysis time (baseline will be set during kickoff).
3. A backlog that engineering can pick up immediately without additional clarification.
If you thrive at the intersection of product strategy, AI tooling, and fast-moving e-commerce, let’s talk about timelines and next steps.