Agentic AI Engineer

RTX•Arlington, VA

1d•$95,500 - $181,700•Onsite

About The Position

For more than 70 years, scientists and engineers in a wide ranging disciplines at RTX BBN Technologies have collaborated to solve real-world problems through research, exploration, development and prototyping. We partner with the best technical talent in academia and industry to challenge the status quo, pioneer new technologies, and create transformative solutions. Our culture enables all employees to find purpose, thrive, and succeed. By creating an environment where all opinions are valued, risk-taking is encouraged, and excellence is rewarded, we allow our employees to do their best, most important work. The following position is to join our BBN Technologies team:

Requirements

Experience in Python, including experience building production-quality systems.
Experience developing agentic or autonomous AI systems.
Experience in latest research in agentic AI, LLM architectures, planning algorithms, or autonomous reasoning.
Experience designing and running experimental evaluations for AI models or agents.
Technical writing skills, including experience authoring research papers, preprints, or detailed technical reports.
Ability to work collaboratively with cross‑functional research and engineering teams.
The ability to obtain and maintain a U.S. government issued security clearance is required.
U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance.

Nice To Haves

Graduate degree in computer science, machine learning, artificial intelligence, or a related field.
Experience with reinforcement learning, multi-agent systems, or cognitive architectures.
Contributions to open-source AI frameworks or agentic toolkits.
Familiarity with cloud-native development, distributed compute, or containerized workflows.
A track record of published research in top AI/ML conferences or journals.

Responsibilities

Design, develop, and deploy agentic AI systems capable of autonomous reasoning, planning, and multi-step task execution.
Build and optimize Python-based frameworks and tools that support scalable agent architectures.
Integrate cutting‑edge research into practical applications, rapidly prototyping new agentic capabilities.
Collaborate with research scientists and engineers to design experiments, evaluate system performance, and produce high‑quality technical documentation.
Lead or contribute to peer‑reviewed publications, white papers, and internal research briefs.
Partner with product and engineering teams to translate research insights into real‑world impact.