Research Engineer

Requisition Id 16618 

­­Overview:  

We are seeking a highly motivated Research Engineer who will support agentic AI workflows, AI infrastructure architectures, and AI-native applications for critical infrastructure resilience projects at ORNL. This position resides in the Critical Infrastructure Resilience (CIR) Group in the Human Dynamics Section, Geospatial Science and Human Security Division, National Security Sciences Directorate, at Oak Ridge National Laboratory (ORNL). 

 

As a Research Engineer, you will contribute to cutting-edge research and development efforts aimed at enhancing the resilience of critical infrastructure systems through AI-enabled decision support, intelligent data agents, retrieval-augmented generation, and scalable machine learning systems. This position offers a unique opportunity to work on interdisciplinary projects in collaboration with leading experts, tackling challenges related to energy, water, cybersecurity, transportation, emergency response, and community resilience. You will have the opportunity to creatively use methods from generative AI, agentic AI systems, computational data science, machine learning, high-performance computing, cloud platforms, and geospatial analytics to help frame and solve these problems on a national and global scale. 

 

The successful candidate will work on advancing AI architectures, data pipelines, model evaluation methods, and production-ready applications that improve understanding of critical infrastructure risks, dependencies, and recovery options. Your research will help inform investments in resilient infrastructure; support AI-enabled planning, restoration, and emergency response workflows; accelerate analysis of heterogeneous infrastructure datasets; and deliver trustworthy, secure, and reproducible AI capabilities for mission-driven sponsors. 

 

The CIR Group is a part of the Geospatial Science and Human Security Division at ORNL. The CIR group is heavily engaged in modeling risk and resilience of critical infrastructures to achieve equitable, reliable and adaptable built environments through data ecosystems creation, data science and integrated complex systems analysis. The group’s vision is to enable a sustainable, safe, and secure critical infrastructure for all. 

 

The National Security Sciences Directorate (NSSD) at Oak Ridge National Laboratory leads scientific and technological breakthroughs to confront some of the nation’s most difficult security challenges. We develop interdisciplinary applications needed for the security of our nation today and target our vision on how these challenges may manifest themselves in a decade or more. NSSD’s research and development focuses on cybersecurity and cyber physical resiliency, data analytics, geospatial science and technology, nuclear nonproliferation, and high-performance computing for sensitive national security missions. We also enhance ORNL contributions to national security challenges by working closely with leading researchers at the lab in areas such as nuclear and chemical sciences and engineering, applied materials, advanced manufacturing, biosecurity, transportation, and computing. 

 

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.

 

Major Duties/Responsibilities:   

• Lead and contribute to the design, development, and implementation of agentic AI workflows, retrieval-augmented generation systems, LLM orchestration patterns, and AI-native applications that improve understanding of critical infrastructure resilience, risk, and recovery. 

• Design and evaluate scalable AI infrastructure architectures for critical infrastructure applications, including data ingestion, vector search, model serving, workflow orchestration, monitoring, and deployment across high-performance computing, cloud, and hybrid environments. 

• Develop intelligent data agents and automated analysis tools that can explore, summarize, validate, and visualize large, heterogeneous datasets while supporting transparent and uncertainty-aware decision-making. 

• Investiga