Vanguard

Adversarial AI Defense, Specialist

United States · Work style not stated · Full time

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About the role

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  • EmployerVanguard
  • LocationUnited States
  • Work styleWork style not stated
  • Employment typeFull time
  • Employer posted

Global Risk and Security (GR&S) at Vanguard enables business strategy, protects client and Vanguard interests (e.g., assets and data), and stewards a strong risk culture. Our teams leverage enterprise-wide insights, deep expertise, and trusted advice so that across Vanguard leaders and crew drive faster, stronger, risk-informed decisions.

Within GR&S, the Enterprise Security and Fraud (ES&F) sub-division is responsible for the global protection of Vanguard crew, property, data, and client assets. We are the trusted advisors that protect the pride of Vanguard with state-of-the-art security and fraud capabilities. We are a world-class destination of highly engaged, passionate, and diverse talent expected to continuously learn and develop in an ever-changing security landscape.

Our crew are our greatest resource – by joining our team you will build collaborative long-term relationships and enjoy a suite of benefits that includes comprehensive health and wellness care, work-life balance, and an investment in your future at its core.

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Responsibilities:

  • Build and lead a first-of-its-kind defensive program focused on countering autonomous systems and adversarial AI, including its charter, operating model, and technical roadmap.
  • Mentor a team of analysts and engineers across reverse engineering, AI-assisted analysis, building depth in a scarce and fast-moving skill set.
  • Identify, test, and validate detective, preventive, and compensating controls built to hold up against AI-driven and autonomous attack techniques, and measure how well they perform under realistic adversary conditions.
  • Design and run deception and canary infrastructure. Identify, test, and validate deceptive controls, then seed, tune, and maintain canary assets that disrupt, misdirect, and neutralize autonomous adversaries and agentic attack tooling.
  • Stand up and maintain a dedicated lab environment to simulate adversarial AI and autonomous attack scenarios and continuously stress-test control effectiveness.
  • Recover, triage, and deconstruct malicious binaries, scripts, and payloads through static and dynamic reverse engineering to determine capability, intent, attribution signals, and autonomous behavior patterns.
  • Build AI-assisted pipelines that automate triage and intelligence extraction at volume, and put that intelligence to work across detection engineering, threat hunting, incident response, and threat intelligence functions.
  • Turn high-value intelligence into automated detection and response workflows that identify, intercept, and disrupt machine-speed attacks before they reach their objective.
  • Map and predict the attack paths autonomous systems and adversarial AI are most likely to take, and use that insight to prioritize where defensive investment goes.
  • Lead AI-enabled breach investigations, including forensic reconstruction of events, root cause analysis, and timeline development across complex, fast-moving intrusions.
  • Work with red team, cloud security, AI/ML engineering, IAM, and enterprise architecture to build defensive requirements into AI adoption at the design stage rather than retrofitting them later.
  • Define KPIs for program maturity, control coverage, and mean time to disrupt, and brief senior leadership and risk committees on the threat landscape and the organization's readiness against it.
  • Map program outcomes to NIST AI RMF, MITRE ATT&CK and ATLAS, OWASP LLM Top 10, and evolving AI governance and regulatory requirements.

Qualifications:

  • Minimum of five years related work experience, with three years of experience in red teaming, adversary emulation, or penetration testing.
  • Undergraduate degree in a related field or the equivalent combination of training and experience
  • Deep malware reverse engineering expertise (x86/x64, .NET, scripting); hands-on incident response and forensic reconstruction; proficiency in Python and automation tooling; working knowledge of LLM/agentic architectures and their attack surfaces; experience building detection or deception capabilities from scratch.

Preferred:

  • Prior threat research or nation-state adversary tracking experience; familiarity with MITRE ATT&CK and ATLAS; experience applying ML to security analytics; published research or conference presentations; GREM, GCFA, OSCP, or equivalent.

Special Factors

Sponsorship

Vanguard is not offering visa sponsorship for this position.

About Vanguard

At Vanguard, we don't just have a mission—we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

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At a glance

  • Employment typeFull time
  • Employer posted
  • Added to ROLIVA
  • Last checked

Skills in this posting

Skills ROLIVA found in the employer’s own description above. A mention is not a requirement.

Python LLM

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