Senior Software Engineer Applied AI

Overview

Idaho National Laboratory is hiring a Senior Software Engineer for Applied AI to work on our Modeling & Tool Development team. Our team works a 9x80 schedule located out of our Engineering Research Office Building (EROB) facility with every other Friday off. You will develop innovative engineered solutions using current and emerging technologies, with a focus on integrating AI/ML capabilities into production systems.

You will apply expertise in software architecture, system design, and machine learning to solve complex problems that advance INL's mission in energy and national security. You will provide technical leadership across projects, mentor junior engineers, and guide research efforts exploring how AI/ML technologies can be effectively applied to real-world challenges. You will report to the manager for our Modeling & Tool Development team.

• Lead architecture and design of complex software systems, including solutions that incorporate AI/ML models and capabilities.
• Plan, develop, and implement software engineering solutions to complex problems and major projects across multiple technology stacks.
• Design and build production systems for deploying AI/ML models, including APIs, data pipelines, and integration with existing platforms.
• Apply software engineering principles, theories, and concepts to develop scalable, maintainable solutions using Python, C++, C#, Type Script, and related technologies.
• Work with relational databases (SQL Server) and No
  
  SQL databases (Mongo
  
  DB, Neo4J) to design robust data architectures.
• Support research initiatives by evaluating emerging AI/ML technologies and providing technical guidance on practical application and integration strategies.
• Collaborate with project teams to establish scope, cost, and schedule estimates for design and development activities.
• Participate in technical reviews at various project phases and provide expert recommendations on architecture, technology selection, and implementation approaches.
• Develop and implement CI/CD pipelines, testing frameworks, and deployment strategies for complex systems.
• Maintain and upgrade existing systems while developing new capabilities that advance organizational mission.
• Create and review methodologies and architectures that establish technical standards and best practices.
• Ensure compliance with INL's safety, security, environmental, health and quality assurance requirements.
• Document activities, systems, and methodologies; write and present technical papers representing INL.
• Provide technical leadership and mentorship to junior engineers, including code reviews, design guidance, and professional development support.
• Utilize expertise to define strategic technical direction and contribute to organizational roadmaps.
• Other duties as assigned.

• Level 4:
  Bachelor's degree in Computer Science, Software Engineering, Computer Information Systems, Data Science, AI/ML, or related field and 9 years of relevant experience.
• Level 5:
  Bachelor's degree in Computer Science, Software Engineering, Computer Information Systems, Data Science, AI/ML, or related field and 14 years of relevant experience.
• Strong foundation in software engineering principles, design patterns, and system architecture.
• Proficiency in multiple programming languages including Python and at least two of: C++, C#, Type Script/JavaScript.
• Experience with relational databases (SQL Server or similar) and No
  
  SQL databases (Mongo
  
  DB, Neo4J, or similar)
• Experience developing and integrating AI/ML models into production environments.
• Experience with RESTful APIs, microservices architecture, and modern development practices.
• Demonstrated ability to lead technical projects and mentor other engineers.
• This position requires the ability to obtain and maintain a Department of Energy "Q" clearance, which requires US Citizenship.

• Experience architecting and deploying scalable systems in cloud (AWS, Azure, GCP) or on-premises environments
• Hands-on experience with ML frameworks (PyTorch, Tensor Flow, scikit-learn) and the ML development lifecycle
• Experience with .NET ecosystem (C#, .NET Core, Entity Framework, ASP.NET)
• Exper…