AI Cybersecurity Engineer

Agilent Technologies

1d•$139,440 - $217,875•Onsite

About The Position

Agilent is seeking an innovative and highly collaborative AI Cybersecurity Engineer to help enable the secure adoption of Artificial Intelligence (AI) technologies across the enterprise. This role will partner closely with business functions, IT organizations, product teams, and Information Security & Risk Management (ISRM) to ensure AI solutions are designed, developed, deployed, and operated securely throughout their lifecycle. The AI Cybersecurity Engineer will play a critical role in evaluating emerging AI technologies, assessing cybersecurity and compliance risks associated with commercial and internally developed AI solutions, and defining practical security controls that enable innovation while managing risk. This position will serve as a advisor to technology and business teams, helping drive secure AI development practices, increase organizational awareness of AI-related risks, and promote secure-by-design principles across enterprise and product AI initiatives.

Requirements

Bachelor's degree in Computer Science, Cybersecurity, Information Technology, Engineering, Data Science, or a related field.
8+ years of experience in cybersecurity, information security, cloud security, application security, security engineering, or related disciplines.
3+ years of experience supporting AI, machine learning, data science, automation, or emerging technology initiatives.
Strong understanding of cybersecurity principles
Experience evaluating security risks associated with commercial SaaS platforms, cloud services, and emerging technologies.
Knowledge of cybersecurity frameworks, security controls, and industry best practices.
Strong communication and stakeholder management skills with the ability to collaborate across technical and non-technical audiences.
Ability to translate complex cybersecurity and AI-related risks into practical business recommendations.

Nice To Haves

Experience securing generative AI platforms, machine learning environments, AI agents, copilots, and AI-enabled applications.
Experience reviewing or implementing AI governance programs, responsible AI frameworks, or AI risk management processes.
Familiarity with AI threat modeling, model security, prompt injection risks, data leakage protections, model integrity, and AI supply chain security.
Experience working with Azure AI Services, OpenAI, Microsoft Copilot, AWS AI services, Google Vertex AI, or similar platforms.
Knowledge of NIST AI Risk Management Framework (AI RMF), NIST Cybersecurity Framework (CSF), ISO 27001, OWASP Top 10 for LLM Applications, and related standards.
Experience in regulated industries such as life sciences, healthcare, medical devices, software, or manufacturing.
Professional certifications such as CISSP, CCSP, CISM, GIAC, Microsoft Security certifications, AI-related certifications, or equivalent.

Responsibilities

Partner with IT, business functions, and product teams to support the secure development and deployment of AI solutions.
Assist with security assessments and risk reviews of commercial AI platforms, AI-enabled products, generative AI solutions, machine learning models, and internally developed AI capabilities.
Support short-term, mid-term, and long-term AI-related initiatives and projects across Agilent.
Collaborate with enterprise architects, cloud teams, engineering teams, and security specialists to integrate security controls into AI solutions.
Participate in threat modeling, architecture reviews, design discussions, and security assessments for AI-enabled systems.
Assist with evaluation of emerging AI technologies, security capabilities, industry trends, and evolving threat landscapes.
Help define and mature Agilent's long-term AI security strategy, governance framework, and security roadmap.
Partner with Legal, Privacy, Compliance, Risk Management, Product Security, and Enterprise Security teams to ensure AI solutions align with applicable requirements and standards.
Develop security recommendations for AI data protection, model security, identity management, access controls, model governance, and third-party risk.
Act as a secure AI evangelist by promoting awareness, education, and adoption of secure AI development practices throughout the organization.
Contribute to executive presentations, strategy discussions, standards development, and governance forums related to AI security.