Vulnerability Management Engineer (AI Automation)
Trellix (company site, opens in a new tab)5+ yrsRemoteDirect career pageEst. 18–30 LPA
Posted 14h ago
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Job description
Structured overview of role & requirements
About This Role
- Own end-to-end vulnerability management across hybrid cloud, container, and application environments, from asset discovery and assessment through remediation verification and executive reporting.
- Build AI-agent workflows to automate discovery, data reconciliation, vulnerability validation and prioritization, ticket routing, SLA escalations, and reporting.
- Set remediation SLAs and exception governance; coordinate critical zero-day response and cross-functional remediation, using threat intelligence and business impact to prioritize risk.
Minimum Requirements
- Work Experience Required: 5+ years in Information Security, focused on Vulnerability Management, Application Security, or Cloud Security.
- Hands-on experience with vulnerability management, CNAPP, and AppSec solutions; production-grade Python automation; and REST or GraphQL APIs.
- Demonstrated experience deploying autonomous AI agents or multi-step LLM workflows, including RAG-based vulnerability analysis and false-positive reduction.
- Experience integrating security tools with ticketing systems and CMDBs; knowledge of CVSS, EPSS, CISA KEV, AWS/Azure/GCP, Docker/Kubernetes, CI/CD, and the stated NIST SSDF, EU CRA, and IEC frameworks.
Ideal Candidate Profile
- Has delivered vulnerability-management programs end to end, including remediation governance, exception handling, zero-day response, and executive metrics.
- Can connect scanner and asset data, source code, threat intelligence, and business criticality to determine practical exploitability and remediation priority.
- Combines security automation and LLM-agent engineering with experience coordinating remediation across IT Operations, DevOps, and Software Engineering.