AI Security Engineer

EY; India; Hybrid; INR 2,600,000 - 4,200,000; Full time

Job summary

EY GDS is seeking a Senior Cyber AI Engineer to lead AI-enabled vulnerability management and security automation within EY's Global Delivery Services. You will design AI security guardrails, perform AI red team assessments, and drive automation and CI/CD integrations for security testing across enterprise environments.

The role emphasizes building AI-driven Cybersecurity capabilities, mentoring teams, and shaping responsible AI usage within cyber operations, with a focus on vulnerability

Qualifications

• 4–8 years in Cybersecurity.
• 2+ years working with AI/ML or Security Automation initiatives.
• Experience leading enterprise Vulnerability Management programs.

Responsibilities

• AI Security & Guardrails: Design, implement, and maintain enterprise AI security guardrails.
• Develop controls to mitigate prompt injection, jailbreaks, data leakage, hallucinations, model abuse, and adversarial attacks.
• Define AI trust, safety, governance, and security standards.
• Evaluate AI applications against security, privacy, and compliance requirements.
• Establish policies and enforcement mechanisms for responsible AI usage.
• Conduct security architecture reviews for AI applications, agents, and autonomous workflows.
• Define secure deployment patterns for LLM, RAG, and agent-based solutions.
• Establish security logging, monitoring, and detection capabilities for AI systems.
• AI Red Teaming: Conduct AI red team assessments against enterprise AI applications.
• Develop adversarial testing scenarios and attack simulations.
• Identify and document vulnerabilities and weaknesses within AI systems.
• Perform threat modeling for AI-enabled business processes.
• Define remediation recommendations and compensating controls.
• Perform AI-focused penetration testing against LLM, RAG, and agentic applications.
• Assess risks related to prompt injection, indirect prompt injection, tool manipulation, excessive agency, data poisoning, and model abuse.
• Execute threat-informed adversarial simulations aligned to MITRE ATLAS and OWASP LLM guidance.
• Engineering & Automation: Develop Python-based automation for AI security and testing workflows.
• Build APIs, integrations, and orchestration frameworks supporting AI evaluation efforts.
• Integrate testing and governance controls into CI/CD pipelines.
• Create dashboards and reporting capabilities that provide visibility into AI risk and performance.
• Integrate AI security controls into DevSecOps and Secure SDLC processes.
• Automate security validation, compliance verification, and security regression testing for AI applications.

Skills

Application Security

DevSecOps

Penetration Testing

Security Architecture

Cloud Security

Identity & Access

Threat Detection

Vulnerability Mgmt

Education

BE / BTech / MTech / MSc / MCA

Job description

Job Title: GDS Cyber - Frontier AI-VMDR - Senior Engineer

At EY, youll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And were counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

Position Tittle: EY GDS Senior Cyber AI Engineer, Technology Consulting:

At EY, were all in to shape your future with confidence.

Well 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.

About Global Delivery Services:

Global Delivery Services refers to EY's worldwide network of service delivery centers. The GDS team plays an important role in EY’s strategy by ensuring effective support to EY’s growth agenda.

Our journey started in 2002 with approximately 200 people. Today we stand at 80,000+ professionals in ten locations around the world. We operate in Argentina, China, Hungary, India, Philippines, Poland, Sri Lanka, Mexico, Spain and the United Kingdom.

Client service is focused on providing Consulting, Assurance, Tax, Strategy & Transactions, and Knowledge support to our clients around the world. The teams enable account teams worldwide to provide seamless, high-quality, value-added support, helping deliver exceptional client service.

Enablement Services provides cost-effective, high-skilled, and innovative services to support EY’s global and local enablement teams. Markets, BMC, AWS, Finance and Accounting, Risk Management, Procurement, People Shared Services, IT Service Delivery and IT Global Infrastructure services, are among the services offered by Enablement Services.

Our innovation specialists serve the GDS Client Service and Enablement Services teams, along with Service Lines, Core Business Services and Sectors. The team brings the desired environment, technologies and skilled teams together for facilitation, rapid prototyping and innovative thinking. The competencies offered include analytics, digital, user experience, mobile technology, infrastructure, Microsoft technologies and open innovation.

Role Overview:

As a Senior Cyber AI Engineer within EY's Global Delivery Services (GDS) Cybersecurity Team, you will drive the convergence of Cybersecurity, Vulnerability Management, and Artificial Intelligence to build intelligent, scalable, and automated security operations.

You will design, implement, and enhance AI-enabled vulnerability management programs that leverage machine learning, generative AI, intelligent analytics, and automation to improve risk identification, prioritization, remediation, and executive decision-making across enterprise environments.

In addition to delivering client engagements, you will help shape EY’s AI-driven Cybersecurity capabilities, contribute to thought leadership, and mentor teams on applying AI responsibly and securely within cyber operations.

The Opportunity

As organizations rapidly adopt AI and cloud-native technologies, cybersecurity teams must evolve beyond traditional vulnerability management approaches. You will help clients transform their security operations by applying AI and data-driven techniques to vulnerability management lifecycle

Key Responsibilities

AI Security & Guardrails

• Design, implement, and maintain enterprise AI security guardrails.
• Develop controls to mitigate prompt injection, jailbreaks, data leakage, hallucinations, model abuse, and adversarial attacks.
• Define AI trust, safety, governance, and security standards.
• Evaluate AI applications against organizational security, privacy, and compliance requirements.
• Establish policies and enforcement mechanisms for responsible AI usage.
• Conduct security architecture reviews for AI applications, agents, and autonomous workflows.
• Define secure deployment patterns for LLM, RAG, and agent-based solutions.
• Establish security logging, monitoring, and detection capabilities for AI systems.

AI Red Teaming

• Conduct AI red team assessments against enterprise AI applications.
• Develop adversarial testing scenarios and attack simulations.
• Identify and document vulnerabilities and weaknesses within AI systems.
• Perform threat modeling for AI-enabled business processes.
• Define remediation recommendations and compensating controls.
• Perform AI-focused penetration testing against LLM, RAG, and agentic applications.
• Assess risks related to prompt injection, indirect prompt injection, tool manipulation, excessive agency, data poisoning, and model abuse.
• Execute threat-informed adversarial simulations aligned to MITRE ATLAS and OWASP LLM guidance.

Engineering & Automation

• Develop Python-based automation for AI security and testing workflows.
• Build APIs, integrations, and orchestration frameworks supporting AI evaluation efforts.
• Integrate testing and governance controls into CI/CD pipelines.
• Create dashboards and reporting capabilities that provide visibility into AI risk and performance.
• Integrate AI security controls into DevSecOps and Secure SDLC processes.
• Automate security validation, compliance verification, and security regression testing for AI applications.

Additional AI Security Skills

• Application Security (OWASP Top 10)
• Secure SDLC / DevSecOps
• Penetration Testing and Red Teaming
• Security Architecture Reviews
• Cloud Security
• Identity and Access Management
• Threat Detection and Monitoring
• Vulnerability Management

Additional Security Frameworks

• MITRE ATLAS
• OWASP Top 10 for LLM Applications
• OWASP ASVS
• NIST AI Risk Management Framework
• NIST Secure Software Development Framework (SSDF)
• Secure AI Development and Governance Frameworks

To Qualify for the Role

Education

• BE / BTech / MTech / MSc / MCA

Experience

• 4–8 years in Cybersecurity
• 2+ years working with AI/ML or Security Automation initiatives
• Experience leading enterprise Vulnerability Management programs

Preferred Certifications

• CEH, CISSP, CISM, OSCP, GIAC, Azure AI, Open AI, AWS ML, Azure ML certifications

What We Look For

Professionals who can bridge the gap between cybersecurity and artificial intelligence by:

• Building AI-enabled cyber defense solutions.
• Automating vulnerability and risk management processes.
• Driving next-generation cyber transformation initiatives.

The ideal candidate combines the mindset of a Security Architect, Vulnerability Management Leader and AI Engineer to create intelligent, scalable, and resilient cybersecurity VM programs.