Full Stack AI Platform Engineer – AI Accelerator

AI Accelerator Engineer

At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world.

Join us and help shape the future of aerospace and defense.

Role Summary The AI Accelerator works across RTX to mature early-stage AI prototypes and deploy them as secure, scalable applications on the AI Factory—RTX's common AI infrastructure. This role is responsible for building enterprise-ready AI solutions based on models and capabilities developed by research and development teams across RTX.

What You Will Do

• Convert AI prototypes into production-grade applications, microservices, and pipelines deployable on the AI Factory.
• Build and deploy cloud-based services on AWS and Azure following RTX best practices.
• Integrate AI/ML models (LLMs, analytics, perception, RAG pipelines) into enterprise applications.
• Implement CI/CD, automated testing, observability, and secure deployment workflows.
• Collaborate with R&D teams to refine prototype functionality for enterprise use.
• Ensure compliance with RTX cybersecurity, infrastructure, and regulatory requirements.
• Participate in architecture reviews, code reviews, and agile development activities.
• Contribute reusable components and patterns that strengthen the AI Factory platform.

Qualifications You Must Have

• Typically requires a degree in Science, Technology, Engineering or Mathematics (STEM) and a minimum of 10 years of prior relevant experience unless prohibited by local laws/regulations.
• Proficiency in Python, C++, and modern back-end frameworks.
• Experience with CI/CD pipelines and Dev Ops automation tools (Git Hub Actions, Jenkins, etc.).
• Familiarity with LLMs, RAG workflows, and AI frameworks (PyTorch, Tensor Flow).
• Familiarity with integrating AI/ML models into software applications.

Qualifications We Prefer

• Knowledge of MLOps practices (model registry, monitoring, pipelines). Experience deploying applications on AWS and/or Azure.
• Knowledge of REST APIs, microservices, SQL databases, and distributed systems.
• Experience with Docker and Kubernetes.
• Experience delivering solutions in regulated or security-conscious environments.
• Strong problem-solving skills, initiative, and ability to define technical direction.

• Strong analytical, problem-solving, written/verbal communication, and interpersonal skills with track record of teamwork, adaptability, innovation, and initiative.
• Clear and effective communication with all levels of management, business development, researchers, and customers.
• Ability to approach open-ended tough problems as an opportunity to innovate.
• Ability to focus on results in a fast-paced, dynamic team environment.
• Ability to work independently with limited direction and in multidisciplinary environment.

This position is classified as:

Hybrid:
Employees who are working in Hybrid roles will work regularly both onsite and offsite. Ratio of time working onsite will be determined in partnership with your leader.

If you live within a reasonable commute of an RTX site with other colleagues you interact with, your manager will discuss whether there is a degree of onsite presence associated with this role.

Candidates will learn more about role type and current site status throughout the recruiting process. For onsite and hybrid roles, commuting to and from the assigned site is the employee's personal responsibility.

The salary range for this role is 132,400 USD - 251,600 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays.

Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance.

This role is a U.S.

-based role. If the successful…