This role pays more than
87%
of similar roles. Most pay
$134,000–$185,500
— the shaded band above.
At the midpoint, this role pays about
$205k
versus about
$160k
for comparable roles.
Based on 240 similar postings.
Employer
About Mastercard
Mastercard is a global technology company in the payments industry, processing transactions between financial institutions and merchants using its extensive network of credit, debit, and prepaid card products. Industry: Payments Technology & Financial Services
Mastercard currently has
116 open roles
on FindRole.
Listed pay typically runs
$122,000–$207,000
across 104 roles with salary data.
Principle, Vulnerability Analyst joins the AI Vulnerability Operations team to transform AI-identified security findings into validated, prioritized, and remediated risk reductions across the software environment. This role involves validating vulnerabilities by reviewing code context, dependency data, application architecture, and runtime exposure to determine if AI-generated findings are exploitable or material. The analyst will partner with engineering and product teams to provide actionable remediation guidance, triage results to eliminate false positives, and verify outcomes through code changes and retest results. Key responsibilities include creating playbooks, mentoring others, and providing feedback to improve AI model precision. Required expertise includes vulnerability management, application security, OWASP, CWE, CVSS, threat modeling, and source code review. The role addresses the challenge of integrating AI-assisted security workflows into large enterprise environments to streamline remediation for high-risk applications.
Validate AI-generated vulnerabilities by analyzing code context, architecture, reachability, and exploitability evidence.
Triage findings to distinguish true positives from false positives and determine appropriate risk levels.
Translate complex AI model outputs into clear, actionable remediation guidance for engineering teams.
Partner with product and engineering teams to drive high-risk vulnerabilities through the full remediation lifecycle.
Verify that code changes and configuration updates successfully resolve identified security issues.
Provide feedback to data and platform teams to improve AI model precision and reduce false positives.
Create playbooks, decision trees, and standard operating procedures to scale AI vulnerability operations.
Prepare executive-ready reports and risk narratives regarding remediation progress and residual risks.
What we're looking for
Strong experience in vulnerability management, application security, secure software development, or security engineering.
Deep understanding of common vulnerability classes, secure coding practices, OWASP, CWE, CVSS, exploitability analysis, threat modeling, and risk-based prioritization.