Vulnerability Management Engineer (AI Automation)

Role Overview

We are looking for a strategic Security Engineer to drive end-to-end vulnerability management, governance, and risk-based prioritization across hybrid, cloud, and containerized environments in alignment with NIST SSDF, EU CRA, and IEC standards. The role focuses on engineering autonomous AI agents to automate asset discovery, finding validation, exploitability analysis, ticket orchestration, and zero-day response.

What You Will Do

Direct continuous asset discovery, vulnerability assessment, remediation verification, and executive reporting across hybrid cloud, container, and application ecosystems. Contextualize vulnerability severity (CVSS) using real-world threat intelligence (EPSS, CISA KEV) and business criticality. Spearhead rapid response protocols for critical zero-day vulnerabilities, implementing interim compensating controls and formal risk-acceptance workflows as required.

Why It Might Be a Fit

Partner with and mentor IT Operations, DevOps, and Software Engineering teams to accelerate remediation and embed security-by-design practices. Define, track, and present key performance indicators (scan coverage, MTTR, SLA adherence, and vulnerability aging) to senior leadership.

Requirements

• 5+ years in Information Security with a strong focus on Vulnerability Management, Application Security, or Cloud Security.
• Extensive hands-on expertise with industry-leading VM, CNAPP, and AppSec solutions—including Tenable, Wiz, Qualys, CrowdStrike, or Snyk—with proven ability to programmatically orchestrate scans, ingest telemetry, and validate remediation.
• Demonstrated experience designing and deploying autonomous AI agents and multi-step LLM workflows using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or OpenAI/Anthropic SDKs to automate discovery, reconciliation, and remediation pipelines.
• Proficiency in leveraging LLMs and Retrieval-Augmented Generation (RAG) architectures to correlate vulnerability data with source code repositories, asset metadata, and exploit intelligence to filter false positives and determine real-world exploitability.
• Strong proficiency in Python for developing production-grade security automation, custom integrations, and consuming or building REST and GraphQL APIs.
• Proven experience integrating security scanners with SOAR platforms, enterprise ticketing systems (Jira, ServiceNow), CMDBs, and collaboration platforms (Slack, Microsoft Teams) for automated ticket creation, routing, reminders, and SLA escalations.
• Deep command of CVSS, EPSS, and CISA KEV methodologies, with experience enriching vulnerability telemetry using threat feeds and business impact assessments.
• Comprehensive understanding of cloud platforms (AWS, Azure, GCP), hybrid enterprise networks, container orchestration (Docker, Kubernetes), and CI/CD pipelines.
• Working knowledge of NIST SSDF, EU CRA, and IEC regulatory frameworks, paired with the ability to build automated executive dashboards tracking MTTR, scan coverage, and SLA compliance.

Benefits

• Retirement Plans
• Medical, Dental and Vision Coverage
• Paid Time Off
• Paid Parental Leave
• Support for Community Involvement

Tagged as: Pipeline Management, Python