[Hiring] Lead AI Security Engineer - Senior Manager @EY

Role Description

We are seeking an AI Security Engineer to own the security posture of EY’s Agentic AI platform end to end. This role exists to make EY’s agentic platform defensible in the most highly regulated client environments in the world, including tax, financial services, audit, and risk.

• Own the platform threat model covering agent autonomy, tool invocation, delegated authority, model and data supply chain, multi-tenancy, and every deployment target from cloud to air-gapped.
• Define the security engineering and control set for every platform layer: infrastructure and boot chain, Kubernetes and cluster fabric, identity and secrets, secure execution and sandboxing, gateway and egress, data and state, delivery pipeline, and telemetry.
• Set the secure-by-default contract so that platform capabilities arrive hardened.
• Own defense against agentic threat classes including direct and indirect prompt injection, jailbreak and instruction hijacking, and more.
• Work with the architecture team to help define the agent authority model.
• Own the sandboxing security standard for agent-generated code execution.
• Secure the model and knowledge supply chain.
• Secure agent-to-agent and tool protocols including MCP and A2A surfaces.
• Lead AI red teaming and adversarial testing.
• Own supply-chain integrity end to end.
• Own admission and runtime policy.
• Define Kubernetes and infrastructure hardening baselines.
• Own tenant isolation assurance.
• Serve as the security authority in client engagements.
• Drive security detection and response for the platform.

Qualifications

• Deep cloud-native security expertise: Kubernetes, container, and infrastructure security at production scale.
• Genuine command of AI and agentic threat models.
• Strong zero-trust and workload-identity foundations.
• Fluency in policy-as-code.
• Software supply-chain security depth.
• Offensive-security instinct.
• Pragmatism about risk.
• Exceptional communication skills.
• Security-as-enablement mindset.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Security, or a related technical field.
• 10+ years in security engineering, security engineering, or offensive security.
• Demonstrable depth in cloud-native and Kubernetes security.
• Hands-on experience with workload identity and secrets management.
• Practical experience securing AI or ML systems in production.
• Threat modelling capability applied to real systems.
• A track record delivering under compliance, security, or regulatory constraint.
• Experience defining ownership boundaries and control contracts.

Ideally, you'll also have

• Software supply-chain security experience.
• Policy-as-code experience with OPA, Kyverno, or equivalent.
• Experience building or leading an AI red team.
• Familiarity with confidential computing and hardware attestation.
• Working knowledge of the OWASP Top 10 for LLM Applications.
• Experience with LLM guardrail and defense tooling.
• Experience securing multi-tenant platforms.
• Detection engineering and incident response experience.
• Client-facing or consulting background.
• Relevant certifications or demonstrable equivalent depth.
• Exposure to regulated industries.
• Contribution to open-source security tooling.

Benefits

• Comprehensive compensation and benefits package.
• Medical and dental coverage.
• Pension and 401(k) plans.
• Flexible vacation policy.
• Time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence.