Why this role is notable

The day-to-day work of red-teaming LLMs for prompt injection and jailbreaks, designing LLM guardrails and RAG security controls, and securing ML pipelines and inference endpoints is a specialized discipline that barely existed as a job category before 2022-2023; it is not a relabeled traditional pentest or AppSec role.

Archetype: Engineering

Job Description

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

Senior: AI Engineer (Cyber Defense AI and Automation)

Join the AI Security practice to independently secure AI/GenAI systems and lead adversarial testing initiatives. The role focuses on protecting AI components across lifecycle and implementing robust controls in enterprise environments.

Your Key Responsibilities

Lead AI red teaming execution including prompt injection, jailbreak and data exfiltration scenarios
Perform AI threat modelling across model, data, and application layers
Design and implement LLM guardrails and RAG security controls
Conduct ML pipeline and model lifecycle security reviews
Secure APIs and AI inference endpoints in cloud environments
Support incident response for AI-specific threats and exploitation attempts
Integrate security controls into AI/ML pipelines and DevSecOps workflows
Collaborate with SOC teams for AI workload detection and monitoring use cases

Skills and Attributes for Success

Strong understanding of ML/GenAI concepts (LLMs, embeddings, pipelines)
Hands-on experience in application security, API security and cloud security
Knowledge of AI attack surfaces (prompt, model, data layers)
Adversarial mindset with ability to simulate real-world attack scenarios
Understanding of OWASP Top 10 and LLM vulnerabilities
Working knowledge of MITRE ATT&CK framework

To Qualify for the Role

3–6 years of experience in cybersecurity, application security or cloud security
Hands-on exposure to AI/GenAI security concepts or implementations
Experience in vulnerability assessment, red teaming or threat modelling
Working knowledge of cloud platforms (Azure/AWS)

Ideally, You’ll Also Have

Hands-on experience with AI security tools such as Garak, PyRIT, LLM Guard
Exposure to adversarial ML tools (ART, Foolbox)
Experience integrating security into MLOps/DevSecOps pipelines
Certifications in cloud or security domains (AZ-500, CEH, etc.)

What We Look For

A self-driven cybersecurity professional with strong technical depth in AI security and the ability to independently drive security testing and implementation for enterprise AI workloads.

What We Offer

Opportunity to work on advanced AI security engagements, exposure to global clients, and continuous learning in AI-led cyber defence and adversarial testing methodologies.

EY | Building a better working world

EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.

Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.

Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

TC-CS-Cyber Architecture- OT and Engineering-Cloud Security-Senior

Generate a McCoy IQ challenge in 30 seconds.

Why this role is notable

Job Description

Core fields

Provenance

Verification trail

LLM enrichment

Key details

Why this role is notable

Job Description

Core fields

Provenance

Verification trail

LLM enrichment