AI Security Specialist/SME
$190,000–$212,080 year
On-siteWashington, District of Columbia, United States or Washington, United States
Job Summary
Lead the development and implementation of SBA's AI security program, including policies, standards, and risk management frameworks aligned with NIST AI RMF and federal executive orders. Conduct AI security risk assessments and reviews for AI systems, evaluating threats such as adversarial attacks, model poisoning, and data integrity issues while developing mitigation strategies. Provide expert guidance throughout the AI system lifecycle, from requirements to operations, and collaborate with data science and application teams to integrate security best practices into development workflows. Develop AI security assessment methodologies, governance documentation, and training programs for personnel and contractors. Monitor the AI threat landscape, serve as the technical SME in engagements with OMB, CISA, and NIST, and lead after-action reviews following security incidents to drive continuous program improvement.
Required Qualifications
- Ability to obtain a Public Trust clearance
- Bachelor's degree in Cybersecurity, Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field from an accredited college or university, OR equivalent combination of education and extensive relevant work experience
- 7+ years of progressive experience in cybersecurity, with significant demonstrated experience in AI/ML security, data science security, or a closely related field within a federal government or large enterprise environment
- Demonstrated expert-level knowledge of AI/ML security principles, adversarial machine learning concepts, and AI-specific threat vectors including model poisoning, adversarial attacks, model inversion, and data integrity threats
- Demonstrated familiarity with federal AI governance frameworks and requirements including NIST AI Risk Management Framework (AI RMF), Executive Order 13960, Executive Order 14110, and applicable OMB AI memoranda and guidance
- One or more of the following certifications: Certified Information Systems Security Professional (CISSP), Certified Information Security Manager (CISM), or equivalent senior-level cybersecurity certification, supplemented by demonstrated AI/ML security expertise
- Exceptional written and oral communication skills in English, with the ability to clearly communicate complex AI security concepts, risk assessments, and strategic recommendations to both technical teams and senior non-technical audiences including agency leadership
- Strong leadership skills with demonstrated experience providing expert technical guidance and oversight on AI security matters to cross-functional teams including security, IT, data science, legal, and program management staff
Desired Qualifications
- Master's degree or Ph.D. in Cybersecurity, Computer Science, Artificial Intelligence, Data Science, or a related field
- Prior experience serving as an AI security SME or advisor supporting a federal civilian agency, preferably the SBA or a similar organization
- Certified Artificial Intelligence Security Specialist (CAISS) or equivalent AI security certification, or active pursuit of same
- Demonstrated experience with AI red teaming, adversarial robustness testing, or AI penetration testing methodologies
- Prior experience serving as an AI security SME or advisor supporting the SBA or a similar federal civilian agency
- In-depth familiarity with SBA's AI initiatives, IT environment, and mission areas, including an understanding of the unique AI security challenges and opportunities associated with SBA's specific use cases and operational context
- Demonstrated experience with AI red teaming, adversarial robustness testing, or AI penetration testing methodologies, including hands-on experience using adversarial machine learning tools and frameworks such as IBM Adversarial Robustness Toolbox (ART), Microsoft Counterfit, or similar
- Advanced knowledge of MLOps practices and platforms and their security implications, including experience integrating AI security controls and testing into ML pipelines and model deployment workflows
- Experience with AI supply chain security considerations, including the security risks associated with pre-trained models, open-source AI libraries, and third-party AI services and APIs
- Familiarity with AI fairness, explainability, and transparency concepts and their relationship to AI security and trustworthiness in a federal government context
- Experience with cloud-based AI/ML platforms and services such as AWS SageMaker, Microsoft Azure Machine Learning, or Google V
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