Retail Engineer
Pubblicato il 15-09-2026 - Commerceclarity in Milano
Retailers still run too much catalog work through spreadsheets and copy-paste: filling missing attributes, adapting products to each marketplace, and keeping thousands of SKUs accurate. CommerceClarity replaces that manual work with AI agents.
As a Retail Engineer, you stay with the customer from discovery through production. You redesign their catalog workflow around agents, build the flows yourself and improve them against the agreed KPIs, working with customers across Italy.
This is a high-ownership seat. You own our most strategic accounts end to end and you set the delivery method the rest of the team runs on. We weigh attitude and the combination over years on paper: the sweet spot is three to six years, and the right builder energy beats seniority.
What you would do Lead agent implementations end to end for enterprise retailers, from kickoff to production, on our DIPE method: design, implement, prove, evolve.
Own our most strategic accounts and the heaviest proofs of concept directly.
Define the success KPIs with the customer,
and build the measurement loop that proves the agents are working.
Design and build the agent workflows, and write the prompt layer that drives them.
Integrate agents with customer systems: PIM, ERP, ecommerce platforms, marketplaces, data warehouses.
Own the run. Monitor, debug, iterate on prompts and flows, and move the numbers over time.
Structure how we deliver, and grow the engineers around you, so the team scales on method instead of drowning.
Feed what you learn back into the product and the agent roadmap.
What we are looking for Three or more years of experience, most of it in consulting or solution delivery. Many of our best fits are management engineers who read a business process and enjoy working with data.
You sit between business and technology. You can redesign a retailer’s catalog workflow and build the agent flow yourself. Not a pure PM, not a pure data engineer.
Prompt engineering sense. You iterate against real data,