AI Summary
We're looking for a Vulnerability Management Analyst to apply real-world security expertise to AI development. Analyze vulnerability reports, classify severity, and generate security-reasoning data. 2+ years of experience in vulnerability management required.
Key Highlights
Analyze vulnerability reports and CVEs
Classify severity and impact
Generate security-reasoning data
Key Responsibilities
Analyze vulnerability reports, CVEs, and exposure scenarios
Classify severity, impact, exploitability, and appropriate remediation strategies
Generate, label, and validate realistic security-reasoning data
Technical Skills Required
Benefits & Perks
Fully remote work
Flexible schedule
Opportunity to work with top research labs
Nice to Have
Experience with tools like Tenable, Qualys, Rapid7, or similar scanners
Background in cloud security, container security, or application security
Job Description
Vulnerability Management Analyst (AI Training)
About The Role
We partner with the world's leading AI research teams and labs to build and train cutting-edge AI models. Now, we're looking for experienced security practitioners to bring real-world vulnerability management expertise into the AI development process.
This is a unique opportunity to apply what you already know — CVEs, exposure analysis, risk prioritization, remediation workflows — and directly shape how AI systems reason about cybersecurity. Your hands-on experience in the field is exactly what's needed to make AI smarter and more reliable in security contexts.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
- Analyze vulnerability reports, CVEs, and exposure scenarios across infrastructure and applications
- Classify severity, impact, exploitability, and appropriate remediation strategies
- Review and evaluate patching, mitigation, and remediation decision-making scenarios
- Generate, label, and validate realistic security-reasoning data used to train and evaluate AI systems
- Apply your real-world judgment to distinguish between theoretical risk and what actually matters in production environments
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- 2+ years of experience in vulnerability management, security operations, or infrastructure security
- Familiar with CVEs, vulnerability scanners, patching workflows, and risk prioritization frameworks (e.g., CVSS, EPSS, SSVC)
- Understands the practical tradeoffs between theoretical risk and operational impact
- A clear, structured, and analytical thinker who communicates findings effectively
- Self-motivated and comfortable working independently on task-based assignments
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- Experience with tools like Tenable, Qualys, Rapid7, or similar scanners
- Background in cloud security, container security, or application security
- Familiarity with frameworks like NIST, CIS, or MITRE ATT&CK
- Prior experience working with AI platforms or data labeling workflows
- Work directly on frontier AI systems alongside top research labs
- Fully remote and flexible — work on your own schedule
- Freelance perks: autonomy, variety, and global collaboration
- Contribute to meaningful work that advances AI's understanding of real-world security
- Potential for ongoing work and contract extension
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