Senior Cyber AI Engineer: Frontier AI for Security

EY; Memphis (TN); On-site; USD 105,000 - 192,000; Full time

Job summary

EY's Cyber AI practice seeks a Cyber AI Engineer at Senior Consultant level. You will work as a forward-deployed engineer applying frontier AI cyber models to security challenges, building, evaluating, and deploying AI solutions from prototype to production with guidance from leaders.

You will partner with client security teams to deploy AI workflows for threat investigation, detection, and remediation, contribute to architecture, code reviews, and reusable components while traveling 25-50% as

Qualifications

• Bachelor's degree and 3–5 years hands-on software engineering with AI/ML.
• Proficiency in Python, APIs, Git, automated testing, and production delivery.
• Experience deploying frontier AI models or LLMs for cybersecurity.

Responsibilities

• Deploy AI workflows for threat investigation, detection engineering, vulnerability analysis, and remediation support.
• Own assigned technical deliverables, estimate tasks, and communicate progress and risks to engagement leaders.
• Contribute to architecture, pair programming, code reviews, and integration troubleshooting.
• Work with model providers and researchers to test cyber capabilities and document deployment findings.
• Develop technical demonstrations, proposals, reusable components, evaluation suites and playbooks.

Skills

Frontier AI models

LLMs

Python

APIs

Git

Automated testing

Production delivery

Model integrations

Education

Bachelor's degree in Cybersecurity, CS, IS or Engineering

Tools

CI/CD

Docker

Kubernetes

AWS/Azure/GCP

Job description

EY's Cyber AI practice seeks a Cyber AI Engineer at Senior Consultant level. You will work as a forward-deployed engineer applying frontier AI cyber models to security challenges, building, evaluating, and deploying AI solutions from prototype to production with guidance from leaders.

You will partner with client security teams to deploy AI workflows for threat investigation, detection, and remediation, contribute to architecture, code reviews, and reusable components while traveling 25-50% as