A resume tells you where someone has been. A job description tells you what a role needs. The RED Signal Match tells you whether the capability signals in both actually align — and what the conversation should focus on.
Paste a resume and a job description. Get a signal alignment score, a per-capability breakdown, and a diagnostic narrative in seconds.
A senior platform engineering candidate evaluated against a Director-level AI infrastructure role. Same inputs a hiring team would use — resume on the left, job description on the right — and the signal alignment analysis below.
B.S. Computer Science, UT Austin, 2011
AWS · GCP · Kubernetes · Terraform · Python · Go · SRE · CI/CD
$310,000 – $420,000 base · Equity · Full benefits
Jordan's Ownership signal is the strongest in the profile — the pattern of inheriting broken systems and choosing not to manage around them is well-evidenced across all three roles. The Kubernetes rebuild at Meridian while maintaining 99.97% availability is exactly the kind of high-stakes, irreversible architectural decision this role requires. That signal is clear.
The gap worth exploring is the AI-specific depth this role demands. Jordan's infrastructure experience is enterprise-grade, but the role requires someone operating at the frontier of GPU compute, distributed training, and ML-specific platform design. The conversation should probe: has Jordan operated in environments where the infrastructure directly shapes model capability, or has the work been more general-purpose cloud and platform engineering?
Learning Agility is the signal to test most rigorously. The 61 score reflects that the resume shows Jordan learning well within known domains — but this role requires learning in motion at a technical frontier that changes faster than most planning cycles. The hiring conversation should surface a specific example of Jordan absorbing a genuinely unfamiliar technical paradigm under time pressure and applying it in production.
The Signal Match evaluates capability signal alignment across all five RED signals — surfacing where the candidate and the role connect, where gaps exist, and what the hiring conversation should actually focus on.
This tool is only as accurate as what you put into it. Credential-based language will produce a credential-based read. Overclaimed experience will produce an inflated result. The most useful output comes from honest, specific inputs — not the most impressive ones. Clean in, clean out.
These tools are powered by Claude, Anthropic's AI. The RED Signal Capability Model™, evaluation framework, and diagnostic methodology are the intellectual property of RED Intelligence Group and Rahsaan E. Diaz, CIR, CDR. The engine executes the framework. The thinking belongs to RED.
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The match isn't a keyword comparison. It's a capability signal evaluation — analyzing what the candidate demonstrates against what the role actually demands across all five RED signals.
Reads the resume for evidence of each RED signal — Judgment, Ownership, Adaptability, Learning Agility, Systems Thinking — based on what the candidate has actually demonstrated.
Reads the job description for the capability signals the role actually requires — explicit or implied — based on the complexity and context of the work described.
Compares the two signal profiles across all five capabilities and produces a score for each — showing where candidate and role connect and where gaps exist.
Produces a diagnostic narrative about what the hiring conversation should actually focus on — not a pass/fail verdict, but a framework for a meaningful evaluation.
Candidates use it to evaluate role fit before applying. Hiring teams use it to prepare for interviews. Both get the same signal intelligence from the same analysis.
The free tool surfaces the signal pattern. The full Signal Match Report — available through a RED engagement — maps every gap, names the questions, and builds the evaluation architecture.
The free tool shows you where capability signals align and where they don't. The RED Talent Intelligence Diagnostic™ examines why — and builds the evaluation architecture to fix it systematically across your entire hiring process.
For growing organizations ready to stop guessing on fit and start building a system that consistently surfaces the right people.