Correspondence studies have found evidence of age discrimination in callback rates forolder workers, but less is known about whether job advertisements can themselves shape the agecomposition of the applicant pool. We construct job ads for administrative assistant, retail, andsecurity guard jobs, using language from real job ads collected in a prior large-scalecorrespondence study (Neumark et al., 2019a). We modify the job-ad language to randomly varywhether the job ad includes ageist language regarding age-related stereotypes. Our main analysisrelies on computational linguistics/machine learning methods to design job ads based on the semantic similarity between phrases in job ads and age-related stereotypes. In contrast to a correspondence study in which job searchers are artificial and researchers study the responses of real employers, in our research the job ads are artificial and we study the responses of real job searchers.