Software Engineer I (Hybrid) Arlington, VA & Cambridge, MA

RTX•Arlington, VA

5d•$62,900 - $119,700•Hybrid

About The Position

RTX BBN’s Analytics and Machine Intelligence department (AMI) is seeking current seniors or recent undergraduate/master’s students for a Research Engineer role focused on AI/ML, with a particular interest in Generative AI (GenAI) and Agentic AI systems. This role is in our Arlington, VA and Cambridge, MA offices. In this role, you will work with researchers and engineers to design, build, test, and transition AI capabilities for real-world applications. We are looking for candidates with strong software fundamentals, curiosity about modern AI systems, and an interest in applying emerging techniques to challenging mission and commercial problems. As a successful candidate, you will contribute to projects spanning the full development lifecycle, including prototyping, implementation, evaluation, and deployment into operational environments. Example areas include LLM-based agentic AI systems, retrieval and reasoning workflows, tool-using agents, ML engineering pipelines, and applied research for high-impact use cases.

Requirements

Bachelor’s degree in Electrical Engineering, Computer Engineering or related Science, Technology, Engineering or Mathematics (STEM) major obtained by start date.
Proficiency in Java, Python, and/or C++
Strong problem solving and analytical skills
Excellent written and verbal communication skills
Ability to problem solve and autonomously troubleshoot
Ability to work in a team environment and collaborate with multiple scientists and engineers
U.S. citizenship is required.
The ability to obtain and maintain a U.S. government issued security clearance is required.
Active and existing security clearance required after day 1

Nice To Haves

Prior RTX internship, co-op, or work experience.
Academic or project experience in AI/ML, data science, or generative AI
Interest in AI/ML, GenAI, Agentic AI systems, and/or Data Science
Experience and/or interest in agentic AI systems, such as tool-using LLMs, orchestration workflows, evaluation/benchmarking, or retrieval-augmented systems
Familiarity with ML development workflows, including experimentation, model evaluation, and pipeline development
Exposure to frameworks like LangChain, LangGraph, Autogen, or similar ecosystems
Knowledge of, experience in, or interest in learning about the aerospace, defense, and intelligence community

Responsibilities

Design, build, test, and transition AI capabilities for real-world applications.
Contribute to projects spanning the full development lifecycle, including prototyping, implementation, evaluation, and deployment into operational environments.
Work with researchers and engineers on AI/ML, Generative AI (GenAI), and Agentic AI systems.
Apply emerging techniques to challenging mission and commercial problems.