Senior Software Engineer/Data Scientist; Training Systems
Listed on 2026-06-02
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer, Data Scientist, Data Science Manager
Description
Leidos is seeking a hands-on Senior Software Engineer / Data Scientist to support the development of modern training, education, 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 Type Script and modern front-end development experience alongside practical AI/ML and data science skills that can be applied to operational training and education 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 Responsibilities
Design, develop, and maintain modern web-based training and learning applications
Build responsive, scalable, and accessible front-end applications using Type Script 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
Basic Qualifications
Bachelor’s degree in Computer Science, Data Science, Software Engineering, Mathematics, Engineering, or related technical field with 8+ years of relevant experience and 15+ years overall experience; additional experience may be considered in lieu of degree
Strong hands-on software engineering experience with Type Script and modern front-end development
Experience with modern front-end frameworks such as React, Next.js, Angular, or Vue
Practical experience applying data science, analytics, or AI/ML techniques to real-world applications
Proficiency in Python and familiarity with common data science and machine learning libraries
Experience integrating applications with APIs, backend systems, and data services
Familiarity with AI/ML workflows including data preparation, model integration, inference pipelines, or analytics processing
Experience using modern AI-assisted software development tools and coding agents within professional engineering workflows
Familiarity with contemporary AI coding ecosystems and developer productivity tools such as Claude Code, OpenAI Codex, Cursor, Open Code, Git Hub Copilot, or similar platforms
Demonstrated ability to effectively leverage AI-assisted development while maintaining sound software engineering fundamentals, debugging practices, testing…
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