Full Stack AI Platform Engineer – AI Accelerator

RTX•East Hartford, CT

4d•$132,400 - $251,600•Hybrid

About The Position

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.

Requirements

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 DevOps automation tools (GitHub Actions, Jenkins, etc.).
Familiarity with LLMs, RAG workflows, and AI frameworks (PyTorch, TensorFlow).
Familiarity with integrating AI/ML models into software applications.

Nice To Haves

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.

Responsibilities

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.