Principal Security Architect - AI and Application Security

Principal Security Architect – AI & Application Security Position Overview We are seeking a highly experienced Principal Security Architect – AI & Application Security to lead the design and evolution of next-generation application security capabilities, with a focus on Generative AI, agentic security models, and intelligent automation. This role sits at the intersection of application security, artificial intelligence, machine learning security, platform engineering, and enterprise architecture. The successful candidate will define scalable security architectures, establish secure development patterns, and drive the adoption of advanced security capabilities across modern software environments. The ideal candidate will bring deep expertise in application security architecture, DevSecOps practices, software supply chain security, and emerging AI security technologies. This individual will partner with engineering, platform, AI/ML, and cybersecurity teams to embed automated, intelligent security controls throughout the software development lifecycle. Hybrid role requiring onsite presence Tuesday–Thursday. Locations available in Charlotte, NC; Dallas, TX; or Malvern, PA. Key Responsibilities AI-Driven Application Security Architecture Define and own enterprise security architecture strategies for AI-enabled application security capabilities, including SAST, SCA, API security, container security, and runtime protection. Design and implement intelligent security solutions leveraging Generative AI and agentic capabilities to analyze source code, dependencies, APIs, and application behavior. Establish secure architecture patterns and best practices for AI-assisted code analysis, dependency intelligence, API threat detection, and automated vulnerability identification. Provide architectural guidance for the secure development and deployment of custom-built AI and agentic applications. Vulnerability Discovery & Intelligent Risk Analysis Architect advanced security solutions that enhance traditional application security capabilities through AI-powered analysis and automation. Develop approaches for context-aware vulnerability prioritization by evaluating exploitability, runtime exposure, business impact, and overall risk. Evaluate emerging AI security tools and technologies, recommending secure integration strategies within enterprise application environments. Improve the effectiveness and scalability of vulnerability management through automation and intelligent analysis. AI & Agentic Application Security Establish security architecture standards for Generative AI and agent-based applications, including: Secure AI orchestration patterns Tool and API invocation controls Data protection strategies Autonomous workflow security AI application risk management Define and promote MLSecOps and AI security practices to strengthen the security posture of AI-enabled development environments. Partner with application development teams to embed security-by-design principles into developer workflows, AI workflows, decision-making processes, and autonomous execution paths. Secure Software Development Lifecycle Enablement Define strategies for integrating AI-driven application security capabilities into CI/CD pipelines, developer platforms, and runtime environments. Provide architectural guidance for application onboarding into security platforms, including scanning services, APIs, gateways, and orchestration frameworks. Create reusable security patterns, standards, and frameworks that enable engineering teams to build secure applications efficiently. Collaborate with DevSecOps and platform teams to reduce security friction while improving overall security maturity. Governance, Risk & Security Leadership Translate complex architectural decisions into clear risk assessments and recommendations for executive leadership and governance stakeholders. Establish metrics and KPIs to measure adoption, effectiveness, coverage, and maturity of AI-enabled security capabilities. Serve as a technical leader and mentor to security architects, application security engineers, and engineering teams. Maintain awareness of emerging threats involving AI security, adversarial machine learning, software supply chain risks, and evolving application security practices. Continuously improve enterprise security architecture strategies based on industry trends and emerging technologies. Qualifications Bachelor’s degree in Computer Science, Engineering, Cybersecurity, or a related technical discipline; equivalent professional experience considered. Extensive experience designing and implementing enterprise application security architectures. Strong understanding of secure software development practices, DevSecOps, CI/CD security integration, and cloud-native application security. Experience with application security technologies such as SAST, SCA, API Security, Container Security, Runtime Application Protection. Experience applying Generative AI, machine learning, or automation technologies within cybersecurity environments. Knowledge of AI security risks, including prompt injection, model misuse, data protection concerns, and adversarial threats. Strong communication skills with the ability to influence technical teams, architects, and executive stakeholders. Preferred Experience Experience developing security architectures for AI-powered or agentic applications. Experience with MLSecOps, AI governance frameworks, or AI risk management practices. Background in enterprise security architecture within large-scale technology environments. Experience mentoring security engineering teams and driving security transformation initiatives. #J-18808-Ljbffr