Cyber - AI Engineer - Manager - Consulting
EY · Philadelphia, PA · 1 mo ago
Hybrid$174k–$290k/yrFull-time
About the role
Location: Anywhere in Country At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.
The Opportunity As a Cyber AI Engineer at the Manager 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 combine hands-on engineering with delivery leadership to build, evaluate, and deploy AI solutions—from prototype to production.
What We Look For We seek hands-on engineers who pair cybersecurity expertise with practical AI delivery. You can build with client teams, improve solutions through testing, and balance model capability with safety and reliability. You bring the leadership to develop teams, own delivery, and build client trust while growing EY's Cyber AI engineering practice.
Responsibilities
- Work with client security and engineering teams to deploy AI workflows for threat investigation, detection engineering, vulnerability analysis, and remediation support.
- 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 Manager, own technical delivery, workstreams, timelines, and budgets while mentoring Senior Consultants and Consultants.
- Stay hands‑on through architecture, pair programming, code reviews, and integration troubleshooting.
- Partner with frontier model providers and researchers to evaluate cyber capabilities and translate deployment findings into engineering requirements.
- Support proposals, demonstrations, thought leadership, and account growth.
- Develop reusable components, evaluation suites, and delivery playbooks.
Skills
- Deep understanding of frontier AI models, LLMs, agentic architectures, and retrieval‑augmented generation for cybersecurity.
- Ability to align Senior Managers, Partners, and client executives on use cases, scope, and engineering requirements.
- 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 on time and within budget, with clear acceptance criteria 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 technical and executive audiences.
- Strong client discovery, demonstration, stakeholder management, and collaboration skills.
- Experience developing engineering teams while remaining hands‑on and accountable for quality.
- Commitment to secure engineering, experimentation, and emerging AI cyber capabilities.
Qualifications
- Bachelor's degree in Cybersecurity, Computer Science, Information Systems, Engineering, or a related field and 5+ years of relevant experience; or a graduate degree and 4+ years.
- Experience must include hands‑on software engineering and at least 1–2 years building or deploying AI/ML solutions.
- Proficiency in Python, APIs, Git, automated testing, and production delivery.
- Experience in one or more of the following 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 leading 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%
- Ideally, you'll also have:
- 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 leading engineering workshops, live prototyping, architecture reviews, and executive demos
- Experience building cyber evaluation datasets, fine‑tuning models, or contributing to open‑source AI or security projects
- Forward‑deployed engineering or consulting experience delivering production solutions and managing client relationships
Benefits
- Professional growth, personal fulfillment, and an inclusive culture
- Medical and dental coverage
- Pension and 401(k) plans
- Wide range of paid time off options
Pay
The salary range for this job is:
- New York City, Boston, and Washington DC Metro Areas, Washington State, and Southern California offices – $173,900 to $290,100
- Bay Area California offices – $181,200 to $302,100
- All other offices locations in the US, including Sacramento – $144,900 to $265,800