Hybrid AI Platform Engineer — Backend & MLOps

RTX; San Jose (CA); Hybrid; USD 108,000 - 205,000; Full time

Benefits offered by this job

Healthcare benefits

Flexible work schedules

Parental leave

Job summary

RTX Enterprise Services seeks an experienced AI Platform Engineer to design, build, and operate reusable software, services, and runtimes for AI/ML across RTX. You will work with AI architects, cybersecurity, data, and application teams to deliver secure, scalable platform capabilities.

The role emphasizes production-grade backend systems, model routing and serving, and end-to-end DevOps in a hybrid, multi-environment setting, including on-prem and cloud.

Qualifications

• University Degree in Computer Science, Software Engineering, Engineering, or related STEM with 8+ years of experience or an Advanced Degree with 5+ years of experience.
• 5+ years of hands-on software engineering experience developing backend services, APIs, distributed systems, cloud platforms, or similar production software.
• Experience designing and building APIs, microservices, distributed services, or other backend platform capabilities.
• Experience with cloud-native engineering including Docker, Kubernetes, CI/CD, and infrastructure-as-code, with deployment on major public clouds.
• Experience with production observability and operations, including logging, metrics, tracing, monitoring, alerting, and reliability.
• Experience with enterprise security concepts including authentication/authorization, IAM, secrets management, and secure integration.

Responsibilities

• Design, develop, and operate scalable backend services, APIs, and distributed platform capabilities for enterprise AI applications.
• Build and integrate AI platform capabilities including model access, routing, gateways, runtimes, lifecycle management, and model serving.
• Develop secure capabilities for identity, authentication, authorization, and secrets management.
• Design and automate deployment across development, test, and production using cloud-native technologies and infrastructure-as-code.
• Build observability capabilities including logging, metrics, tracing, monitoring, alerting, and cost visibility.
• Develop platform capabilities supporting MLOps, model lifecycle management, configuration, and production operations.
• Design platform services for scalability, availability, resilience, performance, security across cloud, hybrid, on-premises, and restricted environments.

Skills

Backend development

Python

Java

APIs & microservices

Cloud-native engineering

Kubernetes

CI/CD

Security concepts

Education

University Degree in Computer Science or related STEM

Advanced Degree in related field

Tools

Docker

Terraform

Job description

RTX Enterprise Services seeks an experienced AI Platform Engineer to design, build, and operate reusable software, services, and runtimes for AI/ML across RTX. You will work with AI architects, cybersecurity, data, and application teams to deliver secure, scalable platform capabilities.

The role emphasizes production-grade backend systems, model routing and serving, and end-to-end DevOps in a hybrid, multi-environment setting, including on-prem and cloud.