AI-based product recommendation system

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

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

Squad Hiring managed, within 24h, the AOR-based hiring of the candidates validated through Squad Challenge, handling contract generation adapted to each developer's country of origin, data validation, and the onboarding process.

The squad brought on 5 profiles (ML engineer, Squad Lead, frontend developer, data engineer, backend developer) working on a stack of Node.js (Fastify), Vue.js, MongoDB, PostgreSQL, GitHub, Azure. The company had no consolidated in-house technical team, so the professionals proposed by Squadmakers, brought on under the AOR model, operated as the product's engineering core from day one. The engagement ran for 17 months in total.