AI Platform Engineer (Hybrid)

Date Posted:

Country:

United States of America

Location:

US-CT-FARMINGTON-0004 4 Farm Springs Rd 4 FARM SPRINGS

Position Role Type:

Hybrid

U.S. Citizen U.S. Person or Immigration Status Requirements:

This job requires a U.S. Person. A U.S. Person is a lawful permanent resident as defined in 8 U.S.C. 1101(a)(20) or who is a protected individual as defined by 8 U.S.C. 1324b(a)(3). U.S. citizens U.S. nationals U.S. permanent residents or individuals granted refugee or asylee status in the U.S. are considered U.S. persons. For a complete definition of U.S. Person go here. Clearance Type: None/Not Required

Security Clearance Status:

Not Required

At RTX the worlds largest aerospace and defense company 185000 great minds are united by purpose and inspired to make a difference solving the worlds most complex problems. With our three market leading businesses world-class operations and investments in research and development we offer capabilities and opportunity no one else can. Together we push the boundaries of known science and find new ways to connect and protect our world. Join us and help shape the future of aerospace and defense.

The following position is to join our RTX Enterprise Services team:

We are seeking an experienced AI Platform Engineer to design build and operate the reusable software services infrastructure and runtime capabilities that enable Artificial Intelligence and Machine Learning solutions to be developed deployed secured observed and scaled across RTX. The ideal candidate combines strong backend software engineering with cloud DevOps and AI platform experience. This is a hands-on engineering role focused on building production platform capabilities not simply deploying infrastructure. You will work closely with AI Architects Applied AI Engineers application teams cybersecurity data and enterprise technology organizations to provide secure and reusable capabilities that accelerate AI adoption across RTX.

What You Will Do

• Design develop and operate scalable backend services APIs and distributed platform capabilities that support 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 capabilities for agent and application identity authentication and authorization secrets management tool access permissions and integration with enterprise systems.

• Design and 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 for AI applications and agentic workloads.

• Develop platform capabilities supporting AI evaluation model lifecycle management MLOps configuration versioning and production operations.

• Design platform 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 solution needs into reusable enterprise platform capabilities and continuously improve the developer experience.

What You Will Learn

• How enterprise AI platforms enable Generative AI machine learning and agentic applications to operate securely and consistently across a global aerospace and defense company.

• How models agents tools identity data evaluation and observability come together as reusable enterprise platform capabilities.

• How AI workloads are designed and operated across commercial cloud hybrid on-premises and restricted computing environments.

• How production agentic systems introduce new engineering challenges around identity tool access runtime governance state observability and operational control.

• How emerging AI platforms orchestration technologies interoperability standards and cloud services can be evaluated and incorporated into enterprise architectures.

• How reusable platform capabilities can reduce duplication and accelerate AI solution delivery across multiple RTX business units.

Qualifications You Must Have

• 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 with 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 cloud-native engineering including Docker Kubernetes CI/CD and infrastructure-as-code and experience deploying applications or services using at least one major public cloud platform.

• Experience with production observability and operations including logging metrics tracing monitoring alerting troubleshooting and reliability.

• Experience working with enterprise security concepts including authentication and authorization identity and access management secrets management network security and secure application integration.

Qualifications We Prefer

• Experience building AI/ML platforms developer platforms internal platforms or shared enterprise software services including experience with AI gateways model serving inference platforms model routing agent runtimes orchestration platforms or model lifecycle capabilities.

• Experience with agentic AI platform concepts including agent registration tool execution Model Context Protocol (MCP) agent identity permissions state lifecycle management or agent observability.

• Experience with vector databases enterprise search retrieval platforms knowledge services feature stores model registries or other AI/ML infrastructure and MLOps model deployment model versioning production monitoring AI evaluation infrastructure or model lifecycle automation.

• Experience operating highly available Kubernetes or distributed application platforms and implementing resilience scalability and disaster-recovery patterns.

• Experience supporting AI or enterprise applications across hybrid cloud on-premises restricted or highly regulated environments and familiarity with AI security Responsible AI cloud architecture principles cost management FinOps or enterprise governance requirements.

• Demonstrated ability to independently solve complex technical problems collaborate across engineering disciplines and influence technical decisions within large-scale software or platform initiatives.

What We Offer

Whether youre just starting out on your career journey or are an experienced professional we offer a robust total rewards package with compensation; healthcare wellness retirement and work/life benefits; career development and recognition programs. Some of the benefits we offer include parental (including paternal) leave flexible work schedules achievement awards educational assistance and child/adult backup care.

Learn More & Apply Now!

Work Location: This is a hybrid role 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.

Please ensure the role type defined below is appropriate for your needs before applying to this role. This position is classified as:

Hybrid: Employees who are working in Hybrid roles will work regularly both onsite and offsite. Ratio of time working onsite will be determined in partnership with your leader.

As part of our commitment to maintaining a secure hiring process candidates may be asked to attendselect steps of the interview process in-person at one of our office locations regardless of whether the role is designated as on-site hybrid or remote.

The salary range for this role is 107500 USD - 204500 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer including but not limited to the role function and associated responsibilities a candidates work experience location education/training and key skills.

Hired applicants may be eligible for benefits including but not limited to medical dental vision life insurance short-term disability long-term disability 401(k) match flexible spending accounts flexible work schedules employee assistance program Employee Scholar Program parental leave paid time off and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement.

Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including but not limited to individual performance business unit performance and/or the companys performance.

This role is a U.S.-based role. If the successful candidate resides in a U.S. territory the appropriate pay structure and benefits will apply.

RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However factors such as candidate flow and business necessity may require RTX to shorten or extend the application window.

RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin age disability or veteran status or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans Readjustment Assistance Act.

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