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Emerging tools such as Game Based Assessments have been valuable in talent screening and matching soft skills for job selection. However, these techniques/models are rather stand alone and are unable to provide an objective measure of the effectiveness of their approach leading to mismatch of skills. In this research study, we are proposing a Theoretical Hybrid Model, combining aspects of Artificial Intelligence and Game Based Assessment in profiling, assessing and ranking graduates based on their soft skills. Firstly, an Intelligent Controller is used to extract and classify the graduate skill profile based on data findings extracted using traditional assessment methods of self-evaluation and interview. With motivation and engagement as a competitive difference, an existing Game Based Assessment (OWIWI) is then used to assess the soft skills of these graduates hence generating a Graduate Profile based on results of the game. Moving forward, a ranking technique is then applied to match the profile to selected job requirements based on soft skills required for the job and the graduate strength. Finally, a comparison analysis is concluded based on the soft skills profile obtained before employment (pre-employment) and objective measure feedback of soft skills obtained after employment (post-employment) to provide a validity check to study the effectiveness of the overall Hybrid Model. Specifically, data obtained from this study can be useful in solving issues of unemployment due to mismatch of soft skills at the Higher Learning Institution level.