A majority of software engineers are male, perhaps, because of the very way that software engineering (SE) roles are advertised is gender biased. Thus far, only word-based checking tools are available to identify gender biases (e.g., ``analyst'' is considered a masculine word). However, such word-based analyses end up identifying the skills required for SE job positions as masculine words, and therefore, not sufficient. In this work, we present a more nuanced mechanism to check for gender bias in SE job advertisements by building on the GenderMag method, which has proven to be successful in gender bias detection in software interfaces. From a survey of 44 software practitioners, we identified 16 factors where male and female participants differ and based on a thematic analysis we derived three SE job applicant persona facets. We verified the facets with a small survey where SE candidates related to the descriptions of those factors. We conducted a pilot study using these facets to evaluate four SE job advertisements and identified gender related biases in two of those.