Senior AI Systems Architect

Leidos

1d•Remote

About The Position

The Leidos Digital Modernization Sector is seeking a highly motivated Senior AI Systems Architect; this position will allow for full time telework from any U.S. based location. POSITION SUMMARY: The Leidos Chief Data & Analytics Office (CDAO) is a new, high-growth organization at the center of the company's technology strategy. Our Operational AI (Ops.AI) division is seeking an experienced and visionary Senior AI Systems Architect to join our team. This role is essential for designing the secure, scalable, and trusted AI infrastructure that underpins our mission-critical solutions. This is an exciting opportunity to leverage your experience to empower Leidos with responsible AI capabilities that accelerate innovation and improve mission outcomes.

Requirements

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.
Demonstrated experience architecting and deploying large-scale AI/ML systems on cloud platforms (e.g., AWS, Azure, GCP).
Expert-level understanding of MLOps principles, CI/CD pipelines, and infrastructure-as-code (IaC).
Substantial understanding of cybersecurity principles as they apply to AI systems.
This position offers flexibility for remote or hybrid work arrangements.
Must be a U.S. Citizen and able to obtain and maintain a security clearance in the future.

Nice To Haves

Experience working within the national security, defense, or intelligence communities.
Professional certifications in cloud architecture (e.g., AWS Certified Solutions Architect - Professional, Azure Solutions Architect Expert).
Deep experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).
Familiarity with defense and federal compliance standards such as DoD IL, FedRAMP, NIST, or CMMC.
Experience with trusted AI frameworks and AI risk management.

Responsibilities

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