Vulnerability Management Engineer (AI Automation)

Overview

Drive end-to-end vulnerability management, governance and risk-based prioritization across hybrid, cloud and containerized environments, and engineer autonomous AI agents to automate vulnerability workflows.

What you'll 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.
• Architect and deploy autonomous AI agents to automate asset discovery, CMDB reconciliation, false-positive elimination, exploitability analysis, intelligent ticket routing, SLA breach escalations and executive reporting.
• Establish and enforce program governance, remediation SLAs and exception management frameworks aligned with NIST SSDF, EU CRA and IEC standards.
• Define, track and present key performance indicators (scan coverage, MTTR, SLA adherence and vulnerability aging) to senior leadership.
• Partner with and mentor IT Operations, DevOps and Software Engineering teams to accelerate remediation and embed security-by-design practices.

What you'll need

• 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.

Details

• Remote, India.