This Statement of Work covers the need for student services to develop AI-driven software solutions for maritime operational challenges. The student will use a software engineering iterative approach to develop and test technical solutions using current engineering tools, such as AI Agent Frameworks, Large Language Models (LLMs), Python, and data visualization dashboards. The work involves developing, testing, and analyzing AI agents and their performance within a simulated operational environment to enhance decision-making for Navy users. The Maritime Agentic Network Topology Assistance (MANTA) project aims to research and develop an AI-driven assistant that leverages a state-of-the-art AI Agent Framework and a DoD Large Language Model (LLM). This development is critical as it will demonstrate how advanced decision aids and mission planning tools can be made accessible to average Navy users without requiring extensive domain-specific training. The project will facilitate seamless interactions between a Maritime Operation Center (MOC) watchstander and a complex network topology planning tool, thereby speeding up the delivery of advanced capabilities to warfighters. This can be achieved by applying engineering techniques at an undergraduate level.
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Job Type
Part-time
Career Level
Intern
Education Level
No Education Listed
Number of Employees
501-1,000 employees