nSenior Software Engineer / Data Scientist

• 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\n
• Strong hands-on software engineering experience with TypeScript and modern front-end development\n
• Experience with modern front-end frameworks such as React, Next.js, Angular, or Vue\n
• Practical experience applying data science, analytics, or AI/ML techniques to real-world applications\n
• Proficiency in Python and familiarity with common data science and machine learning libraries\n
• Experience integrating applications with APIs, backend systems, and data services\n
• Familiarity with AI/ML workflows including data preparation, model integration, inference pipelines, or analytics processing\n
• Experience using modern AI-assisted software development tools and coding agents within professional engineering workflows\n
• Familiarity with contemporary AI coding ecosystems and developer productivity tools such as Claude Code, OpenAI Codex, Cursor, OpenCode, GitHub Copilot, or similar platforms\n
• Demonstrated ability to effectively leverage AI-assisted development while maintaining sound software engineering fundamentals, debugging practices, testing discipline, and secure coding standards\n
• Strong understanding of modern software development practices including Git, CI/CD, automated testing, and agile methodologies\n
• Demonstrated ability to independently design and implement production-ready technical solutions\n
• Strong analytical, troubleshooting, and problem-solving skills\n
• Strong written and verbal communication skills\n
• Must hold an active TS/SCI clearance with Polygraph\n, * Experience supporting training, education, simulation, or learning technology environments\n
• Experience building intelligent tutoring systems, adaptive learning platforms, or analytics-driven training applications\n
• Experience working with large language models (LLMs), generative AI, NLP, or AI-assisted user experiences\n
• Familiarity with AI frameworks and ecosystems such as Hugging Face, LangChain, vector databases, or agentic AI frameworks\n
• Experience developing applications using agentic or AI-accelerated software engineering workflows\n
• Familiarity with AI-enabled developer tooling integrated into modern IDEs, terminals, and CI/CD environments\n
• Experience evaluating, customizing, or operationalizing AI coding agents for enterprise or mission-focused development environments\n
• Experience combining AI-assisted development with modern TypeScript, React, or full-stack application architectures\n
• Experience with data visualization, interactive analytics, or dashboard development\n
• Experience working with learning ecosystems or standards such as SCORM, xAPI, or LMS integrations\n
• Familiarity with Node.js or full-stack application development\n
• Experience deploying applications in cloud or enterprise environments\n
• Experience modernizing legacy applications into modern web architectures\n
• Experience supporting Department of Defense, Intelligence Community, or national security customers\n

n 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.\n \n 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.\n \n \nPrimary Responsibilities\n \n \n

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

• Stay current with emerging front-end, AI/ML, and learning technology trends\n, n \nDesired Candidate Profile\n \n The ideal candidate is:\n \n \n

• A builder and hands-on engineer first\n
• Comfortable owning implementation from concept through deployment\n
• Current on modern front-end and AI-assisted engineering practices\n
• Equally comfortable working across UI, data, APIs, and AI integration layers\n
• Interested in education, training, simulation, or mission learning environments\n
• Able to balance speed, experimentation, and engineering discipline in production systems\n
• Comfortable operating in modern AI-accelerated engineering environments where coding agents and AI-assisted workflows are part of day-to-day software development practices\n