AI Integration Architect – AI Accelerator

About the Role

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, a constrained, regulated production environment.
• Design interfaces and integration patterns that allow independently developed AI capabilities, from varied domains and R&D teams, to plug into the AI Factory, avoiding significant rework per application.
• Own service architecture decisions that enable new AI capabilities to be onboarded, scaled, and retired with minimal rework.
• Partner with the AI Factory infrastructure team to influence platform and infrastructure evolution based on real application demands.
• 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.
• Ensure compliance with RTX cybersecurity, infrastructure, and regulatory requirements.
• 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 12 years of prior relevant experience unless prohibited by local laws/regulations.
• Minimum 5 years in Python, C++, and modern back-end frameworks.
• Minimum 3 years experience with CI/CD pipelines and DevOps automation tools (GitHub Actions, Jenkins, etc.).
• Minimum 1 year with LLMs, RAG workflows, and AI frameworks (PyTorch, TensorFlow).
• Minimum 1 year with integrating AI/ML models into software applications.

Qualifications We Prefer

• Demonstrated experience shipping AI or software systems into regulated or compliance-constrained production environments.
• Experience evaluating and hardening in-flight technical work against production and compliance criteria.
• 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.

Pay

The salary range for this role is 157,200 USD - 298,800 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.

Schedule

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. For onsite and hybrid roles, commuting to and from the assigned site is the employee's responsibility.

Benefits

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. 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.