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About the Role
AI systems are moving from generating content to taking action across data, tools, and business processes. You will make that agency defensible by embedding security throughout the lifecycle, turning emerging threats into practical controls that help teams pursue ambitious AI use cases safely. This is a builder role for someone who enjoys both finding flaws and creating the safer path. You will work alongside product and engineering teams, prove controls under adversarial conditions, and replace one-off reviews with reusable patterns, measurable coverage, clear evidence, and rehearsed ways to respond when systems behave unexpectedly.
Responsibilities
- Set the security direction, owning reusable AI security patterns, control objectives, reference architectures, and threat models aligned to the risk and autonomy of each use case.
- Join builders early, working with teams before key design choices are fixed to identify credible attack paths and shape controls that fit the product and delivery model.
- Design scoped authority by creating practical patterns for identity, access, isolation, approvals, and recovery so tool-using AI acts within clear and enforceable boundaries.
- Protect sensitive information by embedding security across the data lifecycle, preserving confidentiality, integrity, provenance, permitted use, and monitored access.
- Secure the delivery path by integrating automated security tests, policy gates, trusted artifacts, traceable changes, and safe rollback into engineering workflows.
- Test adversarially by running focused red-team exercises against AI-specific abuse cases and converting findings into repeatable tests, stronger platform patterns, and actionable guidance.
- Build runtime protection using end-to-end evidence and behavioral signals to detect abnormal actions, privilege misuse, attempted exfiltration, and degrading controls.
- Strengthen response by supporting vulnerability triage and incidents with clear evidence, containment options, recovery actions, and lessons that improve future designs.
- Advise on residual risk by giving product, security, evaluation, and risk leaders concise technical recommendations while keeping approval and risk-acceptance decisions with accountable owners.
- Build shared capability by creating reference implementations, coaching engineers, and turning production lessons into reusable controls that make the safer path easier to adopt.
Requirements
- 5+ years of relevant experience.
- Substantial experience in product, application, cloud, platform, or detection security, including hands-on ownership of production controls.
- Demonstrated ability to assess complex systems and turn attack paths into practical engineering measures.
- Experience securing modern applications, cloud environments, identities, data, networks, and software delivery pipelines.
- Working understanding of generative and agentic AI, including retrieval, model access, tool use, evaluation, and runtime behavior.
- Experience building or extending security tests, controls, telemetry, reference implementations, or adversarial assessments.
- Evidence of supporting vulnerability or incident response and translating lessons into stronger technical controls.
- A record of partnering with engineers and risk functions to improve security while respecting user value and delivery constraints.
Skills
- Security engineering depth: Strong foundations in application, cloud, platform, identity, data, and software delivery security.
- AI threat judgment: Ability to model how prompts, retrieval, agents, tools, users, and external services create new attack paths and failure modes.
- Control engineering: Experience translating threats into preventive, detective, and responsive measures that engineers can implement and operate.
- Adversarial mindset: Practical skill in red teaming, reproducible testing, vulnerability analysis, detection, and incident learning.
- Automation capability: Ability to build security tests, controls, telemetry, reference components and integrate them into delivery pipelines.
- Pragmatic influence: Clear communication and product judgment, with the ability to explain risk without drama, vagueness, or implied approval authority.
Location
- Anywhere in Country
Work Type
- Hybrid
- Remote
Experience Level
- 5+ years of relevant experience
Education Level
- Bachelor’s Degree in a relevant field
Salary/Compensations
- New York City, Boston, and Washington DC Metro Areas, Washington State, and Southern California offices – $128,400 to $192,500
- Bay Area California offices – $133,600 to $200,600
- All other offices locations in the US, including Sacramento – $106,900 to $176,500
Benefits
- Medical and dental coverage
- Pension and 401(k) plans
- Wide range of paid time off options
- Flexible vacation policy
- Time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence
About the Company
- EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.
- Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.
- EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions.
- Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.
Equal Opportunity
- EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law.
- EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities.