Senior Software Engineer / Data Scientist (Training Systems)

Description Leidos is seeking a hands-on Senior Software Engineer / Data Scientist to support the development of modern training,

, and mission-support applications for national security programs. This role combines applied data science, AI/ML integration, and modern software engineering to build scalable, interactive learning and training systems within classified environments. This is an individual contributor role focused on execution and delivery. We are seeking a technical doer — someone who actively designs and builds production systems, contributes code daily, and works across the full application stack. The ideal candidate brings strong TypeScript and modern front-end development experience alongside practical AI/ML and data science skills that can be applied to operational training and

environments. You will work closely with instructional designers, software engineers, mission stakeholders, analysts, and UX teams to create intelligent, data-driven learning platforms and operational training tools. Primary

Design, develop, and maintain modern web-based training and learning applications Build responsive, scalable, and accessible front-end applications using TypeScript and modern frameworks Develop and integrate AI/ML-enabled capabilities into training and operational support systems Apply data science and analytics techniques to support adaptive learning, user insights, performance analysis, and mission workflows Collaborate with instructional designers and subject matter experts to translate learning objectives into interactive digital experiences Integrate front-end systems with APIs, backend services, AI/ML pipelines, and enterprise platforms Develop reusable UI components, visualizations, and workflows supporting scalable training ecosystems Work with structured and unstructured data sources across enterprise and classified environments Participate in the full software development lifecycle including architecture, implementation, testing, deployment, and sustainment Support deployment and operationalization of AI/ML capabilities within production systems Utilize modern AI-assisted development workflows and coding agents to accelerate software delivery, prototyping, testing, refactoring, and documentation Apply contemporary engineering practices using AI-powered development tools while maintaining strong standards for code quality, security, maintainability, and testing Evaluate and integrate emerging developer tooling and agentic engineering capabilities into team workflows and application development practices Troubleshoot application, integration, and data-related issues across distributed environments Contribute to software engineering standards, reusable frameworks, and development best practices Stay current with emerging front-end, AI/ML, and learning technology trends