Senior AI Platform Engineer — Hybrid, Scalable AI Backend

RTX; Andover (MA); 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, services, infrastructure, and runtimes that enable AI/ML solutions across RTX—this is a hands-on role focused on production platform capabilities.

You will work with AI Architects, Applied AI, security, data, and product teams to deliver secure, scalable platform capabilities, supporting deployment across cloud, hybrid, and on-prem environments.

Qualifications

• University degree in Computer Science, Software Engineering or related STEM with 8+ years of experience.
• 5+ years of hands-on software engineering in backend services, distributed systems, or cloud platforms.
• Experience with cloud-native engineering, Docker, Kubernetes, CI/CD, and infrastructure as code.

Responsibilities

• Design, develop, and operate scalable backend services and APIs for enterprise AI.
• Build AI platform capabilities including model access, routing, and agent runtimes.
• Develop secure identity, authentication, and secrets management for AI apps.
• Automate deployment across dev/test/prod with cloud-native tech and IaC.
• Build observability, logging, metrics, tracing, and cost visibility for AI workloads.
• Collaborate with AI Architecture, Cybersecurity, Data and product teams.

Skills

Backend development

APIs & microservices

Cloud platforms

Kubernetes

CI/CD

Security concepts

Python/Java/C#

Education

Bachelor's degree in CS/Engineering

Tools

Docker

CI/CD tools

Job description

RTX is seeking an experienced AI Platform Engineer to design, build, and operate reusable software, services, infrastructure, and runtimes that enable AI/ML solutions across RTX—this is a hands-on role focused on production platform capabilities.

You will work with AI Architects, Applied AI, security, data, and product teams to deliver secure, scalable platform capabilities, supporting deployment across cloud, hybrid, and on-prem environments.