Senior AI Systems Architect

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. 

PRIMARY RESPONSIBILITIES:
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.  

• 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. 

BASIC QUALIFICATIONS:

• 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. 

PREFERRED QUALIFICATIONS:

• 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. 
   

Come break things (in a good way). Then build them smarter.

We're the tech company everyone calls when things get weird. We don’t wear capes (they’re a safety hazard), but we do solve high-stakes problems with code, caffeine, and a healthy disregard for “how it’s always been done.”

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.