AI Security Engineer - Mid

Koniag Operations Services, LLC (KOS), a Koniag Government Services company, is seeking an experienced AI Security Engineer (Mid) to support a comprehensive enterprise cybersecurity services program for a federal government client. This position requires the ability to obtain and maintain a Minimum Background Investigation (MBI) or higher, PIV credentials, and all requisite IT access authorizations prior to performing work. Primary work will be performed at the client site in Washington DC and approved remote/telework locations.

Benefits include medical, dental, and vision insurance, 401(k) retirement plan, paid time off, paid parental leave, life and disability insurance, flexible spending accounts, commuter benefits, and tuition reimbursement.

This role serves as a key technical contributor responsible for supporting the design, implementation, integration, and governance of Artificial Intelligence (AI) and machine learning capabilities within the client's enterprise cybersecurity ecosystem—including AI-powered threat detection, automated compliance monitoring, machine learning-driven risk assessment, and AI-enhanced Security Information and Event Management (SIEM) capabilities—in alignment with applicable federal AI governance frameworks, NIST guidelines, and agency cybersecurity policies.

The ideal candidate is a technically proficient AI security professional with demonstrated hands‑on experience developing and integrating AI and machine learning solutions within complex federal IT environments. This individual must possess solid expertise in AI security engineering, federal cybersecurity frameworks, and the practical application of AI and machine learning technologies to strengthen enterprise cybersecurity operations, threat detection, incident response, and compliance automation capabilities under the direction of the AI Security Engineer Lead.

The AI Security Engineer (Mid) will serve as a key technical contributor within the program's AI security engineering function, working under the direction of the AI Security Engineer Lead to design, develop, implement, test, and maintain AI-powered cybersecurity capabilities across the client's enterprise environment. This individual is responsible for supporting the full lifecycle of AI security engineering activities—from requirements analysis and solution design through development, integration, testing, deployment, and ongoing optimization—ensuring all AI capabilities are secure, governed, compliant, and effectively integrated into operational cybersecurity workflows.

AI Security Engineering & Implementation

• Support the design, development, testing, deployment, and maintenance of AI-powered security solutions for real-time threat detection, automated incident response, behavioral analytics, and compliance monitoring within the client's enterprise cybersecurity environment.
• Develop and maintain machine learning models for anomaly detection, predictive threat analytics, and automated threat hunting, working collaboratively with the AI Security Engineer Lead and SOC analysts to ensure model outputs are operationally relevant and effectively integrated into SOC workflows.
• Implement and maintain AI-driven SIEM enhancements within platforms such as Microsoft Sentinel, including development of machine learning-based detection rules, behavioral analytics models, User and Entity Behavior Analytics (UEBA) configurations, and automated response playbooks to improve incident detection accuracy and accelerate triage activities.
• Support the integration of AI capabilities into the enterprise cybersecurity tool stack, including SIEM, Endpoint Detection and Response (EDR), threat intelligence platforms, vulnerability management systems, and SOC operational workflows, ensuring seamless data flows, accurate model inputs, and reliable automated outputs.
• Automate cybersecurity workflows using AI and scripting technologies to improve the efficiency and speed of security incident response, vulnerability prioritization, compliance assessment, and risk management activities across the enterprise.
• Develop and implement automated compliance monitoring tools leveraging AI to continuously assess adherence to NIST SP 800-53 controls, FISMA requirements, and agency-specific security standards, reducing manual assessment burden and enhancing continuous monitoring effectiveness.
• Support the implementation of AI-driven risk assessment…