AI-based product recommendation system

The company, an early-stage startup inE-commerce headquartered in Spain, needed to solve this challenge: “aI-basedproduct recommendation system”. The main obstacle was finding profiles withreal experience in the business domain, not just generic knowledge of thestack, and their own selection processes dragged on for weeks without results.On top of this, there were methodological problems in team and projectmanagement: inconsistent agile ceremonies, poor visibility into dependencies,and a delivery cadence that was hard to predict. The context was one ofaccelerated growth, with investment already committed and high expectationsfrom leadership and, where applicable, investors.

Squad Challenge built 5 challenges, oneper position, based on the project's real business case, analyzing an averageof 5 candidates per position (25 in total) and delivering the final shortlistin 3 days.

Squad Hiring managed, within 24h, theAOR-based hiring of the candidates validated through Squad Challenge, handlingcontract generation adapted to each developer's country of origin, datavalidation, and the onboarding process.

The squad brought on 5 profiles (ML engineer, SquadLead, frontend developer, data engineer, backend developer) working on a stackof Node.js (Fastify), Vue.js, MongoDB, PostgreSQL, GitHub, Azure. The companyhad no consolidated in-house technical team, so the professionals proposed bySquadmakers, brought on under the AOR model, operated as the product'sengineering core from day one. The engagement ran for 17 months in total.