AI Systems Architect

The Senior AI Systems Architect will serve as the technical cornerstone for our AI platforms, acting as a key leader within the Ops.AI division. This individual will be responsible for setting the technical vision for our AI ecosystem, translating strategic goals into robust architectural blueprints, and ensuring our systems meet the highest standards of security, compliance, and performance. This position is key to enabling the delivery of trusted and responsible AI capabilities across the enterprise and reports to the Director of Operational AI. \n \n \n

• Architectural Design: Design and oversee the development of enterprise-grade, secure, and scalable AI platforms capable of supporting mission-critical operations. \n
• Technical Strategy: Lead the technical strategy for AI infrastructure, including cloud services, containerization, and MLOps pipelines, to support enterprise-wide AI initiatives. \n
• Standards & Governance: Establish and enforce architectural standards, best practices, and governance for AI/ML systems to ensure consistency and quality. \n
• Stakeholder Collaboration: Collaborate with data scientists, engineers, and program managers to ensure architectural designs meet project requirements and strategic objectives. \n
• Compliance & Security: Ensure mission assurance and full compliance with AI lifecycle management frameworks, including AI risk management and security protocols. \n
• Technology Evaluation: Evaluate and recommend new technologies, tools, and frameworks to enhance our AI capabilities and maintain our competitive edge. \n
• Mentorship: Provide expert guidance and mentorship to development teams on architectural patterns, implementation, and best practices. \n

• Master's degree in Computer Science, Engineering, or a related technical field with 15+ years of professional experience; additional years of experience may be substituted in lieu of a degree. \n
• Demonstrated experience architecting and deploying large-scale AI/ML systems on cloud platforms (e.g., AWS, Azure, GCP). \n
• Expert-level understanding of MLOps principles, CI/CD pipelines, and infrastructure-as-code (IaC). \n
• Substantial understanding of cybersecurity principles as they apply to AI systems. \n
• Must be a U.S. Citizen and able to obtain and maintain a security clearance in the future. \n, * Experience working within the national security, defense, or intelligence communities. \n
• Professional certifications in cloud architecture (e.g., AWS Certified Solutions Architect - Professional, Azure Solutions Architect Expert). \n
• Deep experience with containerization and orchestration technologies (e.g., Docker, Kubernetes). \n
• Familiarity with defense and federal compliance standards such as DoD IL, FedRAMP, NIST, or CMMC. \n
• Experience with trusted AI frameworks and AI risk management.\n