A public job posting does not say that AI screens, assesses or selects applicants

Render an AI-use statement into every published posting whose applicant pipeline uses AI, and archive each posting as published.

In the code that publishes postings (ATS integration, careers-site renderer, job-board feed), look up whether the position's applicant pipeline uses AI screening, assessment or selection (a flag on the requisition set by the pipeline configuration, not by hand) and, when it does, append a fixed AI-use statement to the posting body before publishing; refuse to publish when the flag is unknown. Store a copy of each published posting and its application form, with the publication and take-down dates, for the retention period the law sets (three years in Ontario).

Where it goes: 1 application source code, 3 config and feature flags, 12 repository artifacts, 14 user-facing text.

What reviewers look for: in the posting publisher, a check of the requisition's AI-screening flag and an AI_SCREENING_STATEMENT (or equivalent text naming artificial intelligence) added to the body; the flag derived from the screening pipeline's configuration; an archive write with retention for every published posting.

def publish_posting(req):
    body = render('posting.md', req=req)
    job_board.post(title=req.title, body=body)

AI_SCREENING_STATEMENT = ('We use artificial intelligence to screen and assess applications for this position.')

def publish_posting(req):
    uses_ai = screening_config.uses_ai(req.pipeline_id)   # from the pipeline, not a hand-set field
    body = render('posting.md', req=req)
    if uses_ai:
        body += '\n\n' + AI_SCREENING_STATEMENT
    posting = job_board.post(title=req.title, body=body)
    archive.save(posting, retain_years=3)

Engineering guidance, not legal advice. Each provision below may add its own details (a cadence, a deadline, a required notice element): open it for those.