Cyber - AI Engineer - Senior - Consulting

Location:

Anywhere in Country

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As a Cyber AI Engineer at the Senior Consultant level in EY's Cyber practice, you will work as a forward-deployed engineer, helping clients apply frontier AI cyber models to real security challenges. You will build, evaluate, and deploy AI solutions—from prototype to production with guidance from technical and engagement leaders.

As a Cyber AI Engineer, you will work with client security and engineering teams to deploy AI workflows for threat investigation, detection engineering, vulnerability analysis, and remediation support. You will use retrieval, tool calling, and structured outputs, and build evaluation datasets and test harnesses to measure accuracy, false positives, task completion, latency, and cost.

As a Senior Consultant, you will own assigned technical deliverables, estimate tasks, and communicate progress and risks to engagement leaders. You will contribute to architecture, pair programming, code reviews, and integration troubleshooting while supporting Consultants. You will work with model providers and researchers to test cyber capabilities and document deployment findings. You will also contribute to technical demonstrations, proposals, and reusable components, evaluation suites, and delivery playbooks.

• Practical understanding of frontier AI models, LLMs, agentic architectures, and retrieval-augmented generation for cybersecurity.
• Ability to work with engagement leaders and client teams to translate use cases into engineering tasks.
• Strong software engineering skills to build, test, debug, and deploy production AI applications.
• Experience building model integrations, tool-calling agents, evaluation harnesses, and secure security-platform connections.
• Ability to deliver maintainable solutions against agreed requirements and deadlines, with clear tests and documentation.
• Strong troubleshooting skills across cyber workflows, model behavior, data quality, and production issues.
• Ability to explain model behavior, evaluation results, and security trade-offs to engineers and client stakeholders.
• Strong collaboration, requirements gathering, technical demonstration, and client communication skills.
• Ability to work independently on assigned tasks, seek guidance when needed, and support junior team members.
• Commitment to secure engineering, experimentation, and emerging AI cyber capabilities.

• A bachelor's degree in Cybersecurity, Computer Science, Information Systems, Engineering, or a related field and 3–5 years of relevant experience, including hands‑on software engineering and experience building or deploying AI/ML solutions.
• Proficiency in Python, APIs, Git, automated testing, and production delivery, plus experience in one or more of these areas:
  • Deploying frontier AI models or LLM applications for cybersecurity
  • Building agents, model tool integrations, retrieval pipelines, and evaluation harnesses
  • Security operations, threat investigation, detection engineering, or incident response automation
  • Dev Sec Ops , CI/CD, containers, and infrastructure‑as‑code for AI services
  • Cloud engineering and secure AI deployment on AWS, Azure, or GCP
  • API integration with SIEM, SOAR, EDR, vulnerability management, or code security platforms
  • Application security, vulnerability analysis, secure code review, or automated remediation
• Understanding of prompt injection, data leakage, unsafe tool use, and safeguards informed by OWASP Top 10 for LLMs and…