Overview of Role

We are seeking an experienced AI Security Architect to establish security guardrails and governance frameworks for artificial intelligence deployment across our organization. This critical role will work directly with the AI business deployment team to develop standards, controls, and best practices that enable safe and responsible AI usage at both the employee and developer levels. As we build our AI corporate strategy from the ground up, you will be instrumental in shaping how our organization securely leverages AI technologies while protecting customer data, ensuring regulatory compliance, and mitigating emerging AI-related risks.

Duration: 6 Months, Contract (potential to extend or convert)

Responsibilities

• Design and implement comprehensive AI security architecture, including governance frameworks, data protection controls, model security standards, and usage policies for enterprise AI systems
• Collaborate with the AI business deployment team to establish security requirements and controls for AI applications, ensuring alignment between business objectives and security standards
• Develop and enforce AI usage policies and security guardrails for employees, including guidelines for acceptable use of generative AI tools, prompt engineering security, and data sharing restrictions
• Establish security standards and best practices for AI/ML development teams, covering model training security, data pipeline protection, API security, and secure model deployment
• Conduct AI-specific threat modeling and risk assessments, identifying vulnerabilities such as prompt injection, data poisoning, model theft, adversarial attacks, and privacy leakage
• Define data classification and handling requirements for AI systems, ensuring sensitive customer information and personally identifiable information are appropriately protected in training datasets and model outputs
• Evaluate and recommend AI security tools and technologies, including data loss prevention for AI interactions, AI gateway solutions, model monitoring platforms, and security testing frameworks
• Partner with compliance and legal teams to ensure AI implementations meet regulatory requirements including insurance industry regulations, data privacy laws, and emerging AI-specific legislation
• Create security awareness training programs focused on AI risks, responsible AI usage, and secure development practices for different user personas across the organization
• Develop incident response procedures specific to AI security events, including model compromise, data leakage, and unauthorized AI tool usage
• Monitor the evolving AI security landscape and provide strategic guidance on emerging threats, vulnerabilities, and security best practices
• Establish metrics and reporting frameworks to measure AI security posture and communicate risk to executive leadership

Qualifications

• Bachelor's degree in Computer Science, Cybersecurity, Information Systems, or related field; Master's degree preferred
• 8+ years of experience in information security with at least 3 years in security architecture roles
• Demonstrated experience designing security controls for AI/ML systems, including LLMs, generative AI platforms, or machine learning pipelines
• Deep understanding of AI security risks including prompt injection, model inversion, data poisoning, adversarial attacks, and privacy concerns in machine learning
• Strong knowledge of enterprise security frameworks and standards such as NIST CSF, ISO 27001, SOC 2, and data protection regulations including GDPR, CCPA
• Experience with cloud security architectures, particularly in AWS, Azure, or GCP environments where AI/ML workloads are deployed
• Familiarity with AI development tools and platforms such as OpenAI API, Azure AI Services, AWS SageMaker, or Google Vertex AI
• Excellent written and verbal communication skills with ability to translate technical security concepts to business stakeholders and executive leadership
• Relevant security certifications such as CISSP, CCSP, CISM, or specialized AI security certifications
• Experience in the insurance or financial services industry with understanding of regulatory requirements
• Hands-on experience with AI security tools such as AI firewalls, model monitoring solutions, or DLP platforms with AI capabilities
• Background in machine learning or data science with understanding of model training, evaluation, and deployment processes
• Knowledge of responsible AI principles, AI ethics frameworks, and fairness testing methodologies
• Experience building security awareness programs and training materials for technical and non-technical audiences
• Active participation in AI security communities, research contributions, or speaking engagements on AI security topics