Workforce Readiness · Hiring Calibration
AI Security Hiring Calibration
AI security roles barely existed three years ago. Most hiring managers are posting JDs copied from traditional security, adding “AI” to the title, and running interviews that have nothing to do with the actual work. This workshop fixes that.
Define the real role from the actual work. Rewrite the JD grounded in market data. Build an interview loop your whole panel can run consistently. Score candidates against rubrics that predict real performance in AI security functions — not generic security experience.
Use when
- The JD has everything — AI red team, product security, RAG, agent, governance, and compliance — in one role that no one candidate can fill
- Interviewers are asking traditional security questions for an AI security job
- The hiring panel can't agree on what 'good' looks like for this role
- Labs and credentials are sitting unused because hiring managers don't know how to evaluate them
- You're building a new AI security function and need role architecture before you post anything
- A training platform is standing up an enterprise hiring-readiness feature and needs the methodology
Deliverables
- Role architecture
- JD rewrite
- Interview loop
- Scorecard
- Q&A screen
- Lab/simulation screen recommendation
- Candidate rubric
- Onboarding plan
- Training-path map
Workshop format — and enterprise platform module
As a standalone workshop: a 3–4 hour working session for hiring managers, HR, security leads, and talent teams. Output is a real role definition, rewritten JD, interview loop, scorecard, Q&A screen, lab/simulation recommendations, and a 30/60/90 onboarding plan.
As a white-label enterprise feature: training platforms and cyber ranges can embed the Hiring Calibration methodology as a premium enterprise add-on — giving their corporate customers a structured process for building AI security hiring programs on top of their platform's training data.
Also in Workforce Readiness