AI Security Engineer I

EVERSANA provides commercialization services and solutions to the life sciences industry. The AI Security Engineer I supports the secure, governed, and responsible use of AI, machine learning, and generative AI technologies by assessing risks, implementing controls, monitoring threats, and supporting governance and incident response activities.

Responsibilities:

• Assist in the implementation and maintenance of security controls for Artificial Intelligence (AI), Machine Learning (ML), and Generative AI solutions
• Support security assessments of AI-enabled applications, models, and services to identify vulnerabilities, threats, and misconfigurations
• Participate in threat modeling exercises for AI systems and help identify appropriate security controls and mitigations
• Monitor emerging AI security risks, vulnerabilities, attack techniques, and industry trends, providing recommendations for risk reduction
• Assist with testing and validation of AI security controls, including model protection, data security, and access management measures
• Collaborate with security, data science, engineering, and compliance teams to ensure AI solutions align with organizational security standards, regulatory requirements, and responsible AI principles
• Support governance initiatives related to AI usage, including model inventory management, risk assessments, and policy compliance activities
• Help evaluate and implement security technologies and tools designed to protect AI systems, data pipelines, and cloud-native AI environments
• Contribute to security investigations involving AI platforms and assist with incident response activities related to AI and emerging technologies
• Participate in periodic testing of disaster recovery and business continuity plans for critical AI and business systems
• Document findings, recommendations, and remediation activities in accordance with established security and compliance processes
• Demonstrate a commitment to diversity, equity, and inclusion through continuous development, modeling inclusive behaviors, and proactively managing bias
• Perform other duties as assigned

Requirements:

• • Bachelor's degree in Computer Science, Cybersecurity, Information Systems, Engineering, or related field, or equivalent experience
• • 1-3 years of experience in cybersecurity, cloud security, application security, AI engineering, machine learning operations (MLOps), or related technology disciplines
• • Strong analytical, troubleshooting, and problem-solving skills
• • Foundational understanding of AI/ML concepts, Large Language Models (LLMs), Generative AI technologies, and associated security risks
• • Familiarity with AI security topics such as prompt injection, model abuse, data poisoning, model theft, adversarial attacks, and secure AI development practices
• • Basic understanding of cloud platforms (Azure, AWS, or Google Cloud) and cloud security principles
• • Knowledge of security technologies such as EDR, SIEM, vulnerability management tools, identity and access management (IAM), and security monitoring solutions
• • Ability to communicate technical concepts effectively to both technical and non-technical stakeholders
• • Demonstrated ability to work collaboratively in cross-functional teams
• • Travel – 15% annually
• • Hours – Full-time, 5 days per week
• Office: While performing the essential functions of this job the employee is frequently required to reach, grasp, stand and/or sit for long periods of time (up to 90% of the shift), walk, talk and hear; occasionally required to lift and/or move up to 25 pounds. The noise level in the work environment is usually moderately quiet, with frequent interruptions and multiple demands
• • Exposure to AI/ML development, MLOps platforms, or Generative AI technologies in a professional, academic, or personal project environment
• • Experience with cloud-native AI services such as Azure OpenAI, Azure AI Services, Anthropic Claude, AWS Bedrock, Amazon SageMaker, or Google Vertex AI
• • Familiarity with AI governance, responsible AI frameworks, NIST AI Risk Management Framework (AI RMF), MITRE ATLAS, OWASP Top 10 for LLM Applications, or similar industry guidance
• • Basic scripting or automation experience using Python, PowerShell, or similar languages
• • Industry certifications such as:
• • Security+
• • SC-900, AZ-900, or AI-900
• • SC-200 or SC-300
• • CCSK
• • GIAC Foundational Certifications
• • Other relevant cybersecurity, cloud, or AI security certifications
• • Ability to demonstrate sound judgment, professionalism, and confidentiality
• • Excellent written and verbal communication skills
• • Demonstrated interest in AI security, emerging technologies, and continuous learning
• • Experience supporting cybersecurity projects, security assessments, or governance initiatives