AI Integration Architect - AI Accelerator

AI Solutions 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. What You Will Do 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. 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 year in Python, C++, and modern back-end frameworks. Minimum 3 year 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. Raytheon