Maize is one of the most produced cereals worldwide. Many studies have been conducted to decipher the genetic basis of several traits of agronomic relevance. In crops such as maize, where the commercial varieties are F1 hybrids, the optimal populations to screen would theoretically consist of hybrids. However, researchers often use populations composed of inbred lines, which are arguably insufficient for understanding the mechanisms that play a role in hybrid performances. In this study, we have developed a recombinant intercross (RIX) population by crossing pairs of recombinant inbred lines (RILs) belonging to a multi-parental Advanced Generation Inter-Cross (MAGIC) population to perform QTL mapping using a hybrid genetic background. We phenotyped 214 RIX genotypes along with the MAGIC founder inbreds for 10 agronomic traits, including Fusarium Ear Rot (FER) resistance indexes in two consecutive years. The genotypes of RIXs were reconstructed in silico starting from the corresponding RILs’ reconstructed genotype probabilities. For this task, we used a panel of about 74K SNP markers obtained using Single Primer Enrichment Technology (SPET). Results of the QTL mapping in the hybrid population revealed several genomic regions associated with agronomic traits and FER resistance. Suggestive candidate genes were identified in the mapped intervals. The understanding of their role is currently ongoing. Our findings represent a proof-of-concept that RIX populations are potentially outstanding materials to understand the genetic control of complex quantitative traits in hybrid genetic backgrounds. This kind of resource and the information gathered would provide a future platform to support and accelerate maize improvement.