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Tech Stack
Tools & technologiesCloudCyber SecurityDistributed SystemsDockerJavaKubernetesMicroservicesPython
About the role
Key responsibilities & impact- Design, develop, and operate scalable backend services, APIs, and distributed platform capabilities for enterprise AI applications, models, and agents.
- Build and integrate AI platform capabilities including model access and routing, AI gateways, agent runtimes, lifecycle management, tool integration, model serving, retrieval services, and related enterprise AI services.
- Develop secure identity, authentication and authorization, secrets management, tool access, permissions, and enterprise-system integration capabilities.
- Automate deployment across development, test, and production environments using cloud-native technologies, containers, Kubernetes, CI/CD, and infrastructure-as-code.
- Build observability capabilities including logging, metrics, tracing, monitoring, alerting, execution telemetry, and cost visibility.
- Develop capabilities for AI evaluation, model lifecycle management, MLOps, configuration, versioning, and production operations.
- Design services for scalability, availability, resilience, performance, security, and support across commercial cloud, hybrid, on-premises, and restricted environments.
- Partner with AI Architecture, Applied AI, Application Engineering, Cybersecurity, Data, and product teams to translate needs into reusable enterprise platform capabilities.
- Continuously improve the developer experience and accelerate AI adoption across RTX.
Requirements
What you’ll need- A University Degree in Computer Science, Software Engineering, Engineering, or a related STEM discipline and a minimum of 8 years of relevant professional experience, or an Advanced Degree in a related field and a minimum of 5 years of relevant professional experience.
- A minimum of 5 years of hands-on software engineering experience developing backend services, APIs, distributed systems, cloud platforms, or similar production software.
- Programming experience using Python, Java, C#, or another modern backend programming language.
- Demonstrated experience developing tested and maintainable production software.
- Experience designing and building APIs, microservices, distributed services, event-driven systems, or other backend platform capabilities.
- Experience with Docker, Kubernetes, CI/CD, infrastructure-as-code, and at least one major public cloud platform.
- Experience with production observability and operations, including logging, metrics, tracing, monitoring, alerting, troubleshooting, and reliability.
- Experience with authentication and authorization, identity and access management, secrets management, network security, and secure application integration.
- U.S. Person status required.
- Eligible candidates must reside within commuting distance of Farmington, CT, El Segundo, CA, San Jose, CA, Tucson, AZ, McKinney, TX, Andover, MA, Cedar Rapids, IA, or Charlotte, NC.
- Preferred: experience building AI/ML platforms, developer platforms, internal platforms, or shared enterprise software services.
- Preferred: experience with AI gateways, model serving, inference platforms, model routing, agent runtimes, orchestration platforms, or model lifecycle capabilities.
- Preferred: experience with agent registration, tool execution, Model Context Protocol (MCP), agent identity, permissions, state, lifecycle management, or agent observability.
- Preferred: experience with vector databases, enterprise search, retrieval platforms, knowledge services, feature stores, model registries, AI/ML infrastructure and MLOps.
- Preferred: experience operating highly available Kubernetes or distributed application platforms and implementing resilience, scalability, and disaster-recovery patterns.
- Preferred: experience supporting AI or enterprise applications across hybrid cloud, on-premises, restricted, or highly regulated environments.
- Preferred: familiarity with AI security, Responsible AI, cloud architecture principles, cost management, FinOps, or enterprise governance requirements.
Benefits
Comp & perks- Compensation package
- Healthcare benefits
- Wellness benefits
- Retirement benefits
- Work/life benefits
- Parental and paternal leave
- Flexible work schedules
- Achievement awards
- Educational assistance
- Child/adult backup care
- Medical insurance
- Dental insurance
- Vision insurance
- Life insurance
- Short-term disability
- Long-term disability
- 401(k) match
- Flexible spending accounts
- Employee assistance program
- Employee Scholar Program
- Paid time off
- Holidays
- Annual short-term and/or long-term incentive compensation programs (not guaranteed)