THE POSITION: The AI Security Engineer I supports the security, governance, and responsible use of AI, Machine Learning (ML), and Generative AI technologies across EVERSANA. This role assists with securing AI-enabled applications, models, and data; conducting security assessments; monitoring emerging AI threats; and implementing security controls aligned with organizational policies and regulatory requirements.
Working closely with both IT and business stakeholders, the AI Security Engineer I helps ensure AI solutions are developed, deployed, and operated securely while enabling innovation and managing risk effectively.
ESSENTIAL DUTIES AND RESPONSIBILITIES:Our employees are tasked with delivering excellent business results through the efforts of their teams. These results are achieved by:
- 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.
EXPECTATIONS OF THE JOB:- Travel - 15% annually
- Hours - Full-time, 5 days per week
The above list reflects the general details necessary to describe the expectations of the position and shall not be construed as the only expectations that may be assigned for the position.
An individual in this position must be able to successfully perform the expectations listed above.
QualificationsMINIMUM KNOWLEDGE, SKILLS AND ABILITIES:The requirements listed below are representative of the experience, education, knowledge, skill and/or abilities required.
- 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.
PREFERRED QUALIFICATIONS:- 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.
PHYSICAL/MENTAL DEMANDS AND WORKING ENVIRONMENT:The physical and mental requirements along with the work environment characteristics described here are representative of those an individual encounters while performing the essential functions of this position.
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.
Additional Information 
