Cyber - AI Engineer - Senior - Consulting

EY is a globally connected professional services organization providing consulting, assurance, tax, strategy, and transaction services. The Senior Consultant Cyber AI Engineer will help clients apply frontier AI and cybersecurity models to real security challenges by building, evaluating, and deploying AI solutions from prototype through production. The role also involves owning technical deliverables, supporting architecture and integration work, collaborating with clients and model providers, and contributing to demonstrations, proposals, and reusable engineering assets.

Responsibilities:

• 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

Requirements:

• • 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
• • DevSecOps, 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 MITRE ATLAS
• • Working knowledge of security architecture, identity and access management, data protection, and secure AI operations
• • Experience contributing to client-facing delivery or cross-functional engineering, from requirements through deployment and handover
• • Strong writing, presentation, and technical documentation skills
• • Willingness to travel based on client and business needs; estimated at 25–50%
• • Cybersecurity (e.g., CISSP, CCSP), cloud, engineering, or AI/ML certifications
• • Experience with frontier model providers or cyber-focused model selection, adaptation, and evaluation
• • Experience with agent orchestration, model serving, LLM observability, and CI/CD evaluation gates
• • Knowledge of adversarial testing, AI red teaming, sandboxing, and safeguards for authorized dual-use cyber work
• • Experience with data residency, privacy, model access, and deployment in regulated or restricted environments
• • Experience contributing to engineering workshops, live prototyping, architecture reviews, and client demos
• • Experience building cyber evaluation datasets, fine-tuning models, or contributing to open-source AI or security projects
• • Forward-deployed engineering or consulting experience supporting production deployments and client teams