Cyber - AI-Enabled Vulnerability Management - Manager - Consulting

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As a Manager in AI-Enabled Vulnerability Management, you’ll lead teams and client programs that move organizations from scan-and-patch cycles to continuous threat exposure management (CTEM). You’ll set the strategy for how AI is applied across the vulnerability lifecycle and be accountable for both the risk reduction clients realize and the reusable capability we build along the way.

As a Manager on the Vulnerability Management team, you would:

• Lead the design and delivery of AI-enabled vulnerability and exposure management programs across enterprise environments.
• Own the asset and exposure data foundation and define risk-based prioritization approaches using threat intelligence, exploit prediction, reachability, attack path context, and business criticality.
• Direct the build of AI and agentic workflows that extend beyond ticket creation into orchestrated patching, IaC, and validated remediation.
• Advise clients on vulnerability management controls aligned to regulatory, audit, and industry frameworks.
• Set the standard for how AI output is evaluated and trusted — benchmarking against human baselines and measuring false-positive reduction and time-to-remediate.
• Own AI governance in client environments, including guardrails, human-in-the-loop thresholds, auditability, and client risk acceptance.
• Manage engagement delivery end to end — scope, budget, staffing, risk, and quality — and advise client IT, cloud, and security leadership.
• Build reusable accelerators, reference architectures, and delivery assets, and help shape the offering’s roadmap and go-to-market.
• Lead client efforts to extend vulnerability management to AI systems, covering model, prompt, integration, and supply chain weaknesses.
• Develop executive dashboards and risk metrics that demonstrate exposure reduction, remediation performance, and business impact.
• The ability to set the standard for validating AI output across a team.
• A bias toward building reusable capability over repeatable effort.
• Digital and learning agility in adopting new AI tooling, and in helping teams do the same.
• A platform-agnostic mindset, evaluating tooling based on client need rather than a single vendor stack.
• The ability to lead, develop, and retain high-performing teams while remaining accountable for quality.
• The ability to engage senior client stakeholders and escalat risks and opportunities appropriately.

• 6+ years of relevant experience in vulnerability or exposure management, with some in professional services or similar. No bachelor’s degree is required.
• Demonstrated leadership experience managing and mentoring teams and owning delivery quality across concurrent work streams.
• Hands-on experience leading enterprise VM programs across the full lifecycle, using platforms such as Tenable, Qualys, Rapid7, Wiz, Microsoft Defender, or equivalent.
• Production experience applying AI or machine learning to vulnerability management at scale, including guiding teams in doing the same.
• Experience contributing to business development and offering development — proposals, pursuits, or building new service offerings.
• Experience defining evaluation or benchmarking approaches for AI-assisted security workflows.
• Experience establishing governance for AI used in client environments.
• A relevant certification in AI security, vulnerability management, or cybersecurity, or the ability to acquire one after employment.
• Experience assessing or securing AI and machine learning systems.
• Experience defining VM metrics, KPIs, and executive dashboards that demonstrate risk reduction.
• Profi…