Join EY's Global Delivery Services as a Senior Cyber AI Engineer and play a pivotal role in integrating Cybersecurity, Vulnerability Management, and Artificial Intelligence. You will architect and implement sophisticated AI-driven security operations that enhance risk identification, prioritization, and remediation across diverse enterprise environments. This role offers a unique opportunity to contribute to EY's cutting-edge AI-powered cybersecurity capabilities, shape thought leadership, and mentor teams on responsible AI application in cyber defense.

As organizations increasingly adopt AI and cloud technologies, this position is crucial for transforming security operations. You will leverage AI and data-driven methodologies to revolutionize the vulnerability management lifecycle, ensuring clients remain secure in a rapidly evolving digital landscape.

Design and deploy Retrieval-Augmented Generation (RAG) solutions and AI agents for enhanced vulnerability lifecycle management. Build predictive models to pinpoint high-risk assets and anticipate exploitation paths. Develop intelligent remediation orchestration, integrating seamlessly with existing toolsets.

Implement AI-driven exception and exemption processes for cloud, databases, containers, APIs, and web applications. Create AI-assisted vulnerability prioritization models based on industry best practices. Develop AI-powered automation workflows and Generative AI use cases for reporting and analysis.

Lead enterprise-scale Vulnerability Management programs using platforms like Qualys, Tenable, and Tanium. Mentor junior engineers in cyber analytics and AI technologies. Research emerging threats and next-generation cyber defenses. Contribute to solution development, proposals, and thought leadership.

Possess strong experience in Machine Learning, Generative AI, LLMs, AI Security, Prompt Engineering, Vector Databases, Embedding Models, and Agentic AI Frameworks. Proficiency in scripting/programming languages such as Python and PowerShell is essential.

Demonstrate experience with AWS, Azure, and GCP security, alongside hands-on expertise in LLM prompt engineering, platform build, design, and implementation. A deep understanding of the Vulnerability Management Lifecycle and major operating systems (Windows, Linux, UNIX) is required.

Exhibit a thorough understanding of TCP/IP network protocols, network security, and common attack vectors. Familiarity with the latest security vulnerabilities, exploit techniques, OWASP Top 10, and cloud security architecture is crucial. A minimum of 5-8 years in Cybersecurity, with at least 2 years focused on AI/ML or Security Automation initiatives, is necessary. Previous experience leading enterprise Vulnerability Management programs is highly valued.