Digital and AI Software Engineer

Join our team here in the Nuclear Science and Technology directorate at Idaho National Laboratory to design, develop, and enhance cutting-edge data management and AI ecosystem tools. In this role, you'll work on data frameworks, digital twins, and AI/autonomy capabilities that directly support programmatic and research goals across the nation’s leading Nuclear Energy Laboratory. You'll help advance data-for-AI strategies, digital thread and digital twin integration, and agentic AI workflows.

You will be shaping the future of how our organization builds and deploys intelligent systems.

• Design, develop, and improve the Deep Lynx data management and AI ecosystem, including its data frameworks, digital twin capabilities, and supporting infrastructure.
• Architect digital systems that structure, integrate, and contextualize data for AI, machine learning, and autonomous systems - ensuring data is discoverable, trustworthy, and ready for downstream models and agents.
• Build and support agentic AI workflows and other AI/ML-driven capabilities within Deep Lynx and related digital twin and autonomy applications.
• Apply full-stack development skills across web, desktop, embedded, and hosted platforms to deliver solutions that support programmatic and research goals.
• Implement Dev Ops best practices (CI/CD, containerization, cloud and on-premise deployment) to support scaling and maintenance of Deep Lynx and related applications.
• Follow modern software development practices - agile methodologies, version control, code review, and iterative delivery.
• Ensure robust testing (unit, integration, system) and maintain clear, up-to-date technical documentation for architecture, APIs, and workflows.
• Support integration of modeling and simulation capabilities into complex digital systems (e.g., digital twins) that enable autonomy, contributing to domain-specific development (nuclear, chemistry, critical infrastructure, energy delivery/security) as needed.
• Analyze, test, and maintain data frameworks and simulation-based systems to ensure reliability, performance, and technical validity.
• Develop system designs, requirements documentation, and program software using languages such as C#/C/C++, Rust, Python, and Type Script.
• Provide technical consultation to internal teams on data architecture, AI integration, and testing practices.
• Contribute to technical publications, conference papers, and reports.
• Stay current with emerging data, AI, and autonomy technologies.
• Collaborate with high performing scientists and engineers across INL.

• Ability to evaluate and select technical approaches for complex data and software systems
• Strong grasp of software engineering principles as applied to data management, architecture, and visualization
• Knowledge of data architecture and modeling principles, including structuring data for AI/ML consumption
• Familiarity with AI/ML concepts, including agentic AI workflows and their real-world integration
• Working knowledge of Dev Ops and modern development practices (agile, version control, CI/CD, containerization)
• Strong communication skills - able to translate technical concepts for both technical and non-technical audiences
• Excellence collaboration skills and growth mindset.

• Level 1:
  Bachelor's degree in Computer Science, Data Science, Data Engineering, Mathematics, Statistics, or a related field.
• Level 2:
  Bachelor's degree in Computer Science, Data Science, Data Engineering, Mathematics, Statistics, or a related field and 2 years of relevant experience, or an advanced degree in the same fields.
• Hands‑on experience with containerization technologies (Docker, Kubernetes).
• Proficiency in C# and Python.

• AWS, Azure, or related…