This thesis addresses the critical challenge of executing variational quantum algorithms on noisy intermediate-scale quantum (NISQ) devices by developing and validating a custom error-detection architecture. This architecture is based on the [4,2,2] encoding scheme, which in our case is specifically tailored for the Quantum Approximate Optimization Algorithm (QAOA) and applied to the portfolio optimization problem. The methodology first employed the max-cut problem (4 node ring graph) as a pilot case. The encoded circuit successfully reproduced the known optimal bitstrings (0101 and 1010), confirming the correct implementation of the custom [4,2,2] encoding and decoding logic. This required implementing a dedicated library of redefined quantum gates and a decoding function to remap the sampled physical states back into the original logical code space.