Job description

Leidos is seeking a hands-on AI 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 TypeScript 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 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 Basic Qualifications Bachelor’s degree in Computer Science, Data Science, Software Engineering, Mathematics, Engineering, or related technical field with 12 years of relevant experience or a Master s degree with 10 years experience. Additional experience may be considered in lieu of degree Strong hands-on software engineering experience with TypeScript 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, OpenCode, GitHub Copilot, or similar platforms Demonstrated ability to effectively leverage AI-assisted development while maintaining sound software engineering fundamentals, debugging practices, testing discipline, and secure coding standards Strong understanding of modern software development practices including Git, CI/CD, automated testing, and agile methodologies Demonstrated ability to independently design and implement production-ready technical solutions Strong analytical, troubleshooting, and problem-solving skills Strong written and verbal communication skills Must hold an active TS/SCI clearance with Polygraph Preferred Qualifications Experience supporting training, education, simulation, or learning technology environments Experience building intelligent tutoring systems, adaptive learning platforms, or analytics-driven training applications Experience working with large language models (LLMs), generative AI, NLP, or AI-assisted user experiences Familiarity with AI frameworks and ecosystems such as Hugging Face, LangChain, vector databases, or agentic AI frameworks Experience developing applications using agentic or AI-accelerated software engineering workflows Familiarity with AI-enabled developer tooling integrated into modern IDEs, terminals, and CI/CD environments Experience evaluating, customizing, or operationalizing AI coding agents for enterprise or mission-focused development environments Experience combining AI-assisted development with modern TypeScript, React, or full-stack application architectures Experience with data visualization, interactive analytics, or dashboard development Experience working with learning ecosystems or standards such as SCORM, xAPI, or LMS integrations Familiarity with Node.js or full-stack application development Experience deploying applications in cloud or enterprise environments Experience modernizing legacy applications into modern web architectures Experience supporting Department of Defense, Intelligence Community, or national security customers Desired Candidate Profile The ideal candidate is: A builder and hands-on engineer first Comfortable owning implementation from concept through deployment Current on modern front-end and AI-assisted engineering practices Equally comfortable working across UI, data, APIs, and AI integration layers Interested in education, training, simulation, or mission learning environments Able to balance speed, experimentation, and engineering discipline in production systems Comfortable operating in modern AI-accelerated engineering environments where coding agents and AI-assisted workflows are part of day-to-day software development practices If you re looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We re not hiring followers. We re recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We re already at step 30 — and moving faster than anyone else dares. Original Posting: October 19, 2026 For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range: Pay Range $131,300.00 - $237,350.00 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.

Requirements

Must-haves

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.
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

Nice-to-haves

Experience supporting training, education, simulation, or learning technology environments
Experience building intelligent tutoring systems, adaptive learning platforms, or analytics-driven training applications
Experience working with large language models (LLMs), generative AI, NLP, or AI-assisted user experiences
Familiarity with AI frameworks and ecosystems such as Hugging Face, LangChain, vector databases, or agentic AI frameworks
Experience developing applications using agentic or AI-accelerated software engineering workflows
Familiarity with AI-enabled developer tooling integrated into modern IDEs, terminals, and CI/CD environments
Experience evaluating, customizing, or operationalizing AI coding agents for enterprise or mission-focused development environments
Experience combining AI-assisted development with modern TypeScript, React, or full-stack application architectures
Experience with data visualization, interactive analytics, or dashboard development
Experience working with learning ecosystems or standards such as SCORM, xAPI, or LMS integrations
Familiarity with Node.js or full-stack application development
Experience deploying applications in cloud or enterprise environments

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimltypescriptreactnext.jsangularvuepythonmachine learningci/cdagilenode.js

Platform: workday
Effort: long