Considering the exponentially rise in non-linear signal filtering purposes, in this paper a novel parametric continuously programmable infinite impulse response (CPIIR) filter has been developed. Realizing the key upsurging significance of non-linear audio signal filtering, our proposed CPIIR filter model has been realized over parametric equalization system, which can have one or multiple IIR filters in cascade-design to perform continuous filtering. Structurally, our proposed model represents a PE solution containing shelving and second-order peaking CPIIR filters whose design parameters are optimized dynamically by reducing cost-function iteratively. Unlike classical approaches where merely filter coefficients are changed manually to cope up with non-linear signal filtering, our proposed parametric IIR filter employs sum-of-square error (SSE) as the costfunction to update filter design parameters like gain parameter, frequency and bandwidth. Noticeably, the use of SSE as cost-function intends to reduce error (i.e., difference between the target signal and the system frequency response) to optimize global gain parameter that eventually help updating other design parameter adaptively over different frequency-bins or windows. This process retains system response near 0-dB line and thus maintains optimal filtering performance over swiftly varying signal response. Unlike major at hand meta-heuristic based search approaches for parameter tuning, our proposed model applies simple grid search concept that avoided significantly large computation and hardware requirements. MATLAB based simulation with Gaussian white noise embedded non-linear signals reveals that the proposed parametric CPIIR model can achieve optimal filtering performance and suitability towards hardware implementation.