Senior AI Platform Engineer | Cloud & MLOps (Hybrid)

RTX; Charlotte (NC); Hybrid; USD 108,000 - 205,000; Full time

Job summary

RTX is seeking an experienced AI Platform Engineer to design, build, and operate reusable software and services enabling enterprise AI across RTX. You will work with AI Architects, Applied AI, cybersecurity, data, and product teams to deliver secure, scalable platform capabilities.

The role emphasizes hands-on backend engineering, cloud-native deployment, and production readiness across hybrid and on‑prem environments, with a focus on model serving, governance, and tool integration.

Qualifications

• University Degree in Computer Science, Software Engineering, Engineering, or related STEM with 8+ years of experience, or Advanced Degree with 5+ years.
• 5+ years hands-on software engineering in backend services, APIs, distributed systems, cloud platforms, or similar production software.
• Proficiency in Python, Java, C#, or equivalent backend language with production-grade code.
• Experience designing APIs, microservices, distributed services, or backend platform capabilities.
• Cloud-native engineering experience: Docker, Kubernetes, CI/CD, and IaC; deployment on major cloud platforms.
• Proven observability and operations experience: logging, metrics, tracing, monitoring, alerting, reliability.
• Knowledge of enterprise security concepts: authentication, authorization, identity management, secrets management, secure integration.

Responsibilities

• Design, develop, and operate scalable backend services, APIs, and distributed platform capabilities.
• Build and integrate AI platform capabilities including model access, routing, gateways, runtimes, lifecycle management, and model serving.
• Develop secure identity, authentication and authorization, secrets management, and tool access for enterprise systems.
• Automate deployment across dev/test/prod using cloud-native tech, containers, Kubernetes, CI/CD, and IaC.
• Build observability capabilities: logging, metrics, tracing, monitoring, alerting, telemetry, and cost visibility.
• Support AI evaluation, model lifecycle management, MLOps, configuration, versioning, and production ops.
• Design services for scalability, availability, resilience, performance, security across cloud/hybrid/on-prem environments.
• Collaborate with AI Architecture, Applied AI, Application Engineering, Cybersecurity, Data, and product teams to deliver reusable enterprise platform capabilities.

Skills

Backend software engineering

Python

Java

C#

APIs & microservices

Cloud-native engineering

Docker

Kubernetes

CI/CD

Infrastructure as Code

Observability

Security concepts

Education

Bachelor’s degree in CS/Engineering or related STEM

Advanced degree (MS/PhD) in related field

Tools

Docker

Kubernetes

CI/CD

Job description

RTX is seeking an experienced AI Platform Engineer to design, build, and operate reusable software and services enabling enterprise AI across RTX. You will work with AI Architects, Applied AI, cybersecurity, data, and product teams to deliver secure, scalable platform capabilities.

The role emphasizes hands-on backend engineering, cloud-native deployment, and production readiness across hybrid and on‑prem environments, with a focus on model serving, governance, and tool integration.