Sr Cybersecurity Engineer- AI and Model Security

Job Summary

Secure AI and model ecosystems by defining architecture, implementing controls, assessing risk, and supporting resilient deployment and operations.

Responsibilities

• Develop and maintain the organization s AI and model security architecture, standards, roadmap, and governance framework.

• Design, implement, and integrate security controls across the AI/ML lifecycle, including development, DevSecOps, deployment, and operations.

• Assess AI/ML and LLM solutions for risks such as prompt injection, data leakage, adversarial attacks, model manipulation, insecure integrations, and unauthorized access.

• Conduct security testing, architecture reviews, threat modeling, control validation, and incident investigations for AI systems.

• Define and enforce secure configuration and security requirements for AI platforms, models, datasets, APIs, cloud services, containers, and third-party providers.

• Support the selection, deployment, configuration, lifecycle management, and oversight of enterprise AI models, LLMs, and related platforms, including inventories, ownership, approved uses, and controls.

• Establish monitoring capabilities to detect model misuse, abnormal behavior, data exposure, configuration drift, and emerging threats.

• Translate AI security risks into actionable recommendations, contribute to risk assessments and compliance activities, and stay current with evolving threats, regulations, frameworks, and industry best practices.

  Education

• Bachelor s degree in computer science, information systems, engineering, or an equivalent technical discipline or combination of education and relevant experience

  Skills and Competencies

• 4+ years of experience in a technical, engineering, architecture, cybersecurity, or related role

• Demonstrated ability to design, secure, or operate cloud-based solutions, including experience with at least one major cloud platform and its configuration-management capabilities

• Working knowledge of artificial intelligence, machine learning concepts, model lifecycles, application programming interfaces, and large language model technologies

• Experience conducting security architecture reviews, threat modelling, technical risk assessments, or security testing

• Ability to translate strategic objectives and technical AI risks into implementable requirements, controls, and practical recommendations for varied stakeholders

• Hands-on capability with relevant scripting, automation, cloud, security, or machine-learning tools, supported by strong analytical, written, verbal, and cross-functional collaboration skills

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