Vehicle-to-everything (V2X) services are attracting a lot of attention in the research and industry communities due to their applicability in the landscape of connected and autonomous vehicles. Such applications have stringent performance requirements in terms of complex data processing and low latency communications which are utilized to ensure road safety and improve road conditions. To address these challenges, the placement of V2X applications through leveraging of edge computing paradigm, that distributes the computing capabilities to access points in proximity to the vehicles, presents itself as a viable solution. However, the realistic implementation of the edge enabled V2X applications is hindered by the limited computational power provided at the edge and the nature of V2X applications that are composed of multiple independent V2X basic services. To address these challenges, this work targets the efficient placement of V2X basic services in a highway scenario subject to the delay constraints of V2X applications using them and the limited computational resources at the edge. To that end, this work formulates a binary integer linear programming model that minimizes the delay of V2X applications while satisfying the resource requirements of V2X basic services. To demonstrate the soundness of the approach, simulations with varying vehicle densities were conducted, and the results reported show that it can satisfy the delay requirements of V2X applications.