The rapid growth of urbanization worldwide necessitates reliable infrastructure and efficient support structures like utility bridges and tunnels. However, the design of such structures has often been neglected, resulting in inconsistent standards and technical specifications. Typically, utility bridges are constructed first, and service lines like power cables and pipelines are later pulled through them, which can be a tedious process. An alternative approach involves using deployable structures with cables already placed inside, allowing for easy deployment across hindrances, such as the stream. The tensegrity concept offers a lightweight, sturdy, and deployable bridge that can be used temporarily with unique benefits like modifiable stiffness and easy dismantling. Tensegrity structures consist of strings and struts that act as dedicated tension and compression members and are characterized by their self-stressed configurations. To achieve these configurations, the cables must be pre-tensioned, requiring a form-finding approach to find the member prestresses. This study develops a Genetic Algorithm (GA)-based form finding approach that identifies a tensegrity module that complies with tensegrity properties and satisfies structural and constructional requirements. The GA combines the identified self-stressed states to create a tensegrity module capable of withstanding external operational loads while being internally stable. The resulting tensegrity bridge is compared against traditional utility bridges, highlighting its potential benefits and real-life applicability. The study concludes that a tensegrity concept is an efficient approach for utility bridge design.