AI Architect (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 Architect to define and guide the architecture of enterprise Artificial Intelligence and Machine Learning solutions across RTX. This role will partner with business units product teams engineering organizations domain architects cybersecurity data and enterprise technology teams to translate complex business needs into scalable secure and production-ready AI architectures. The ideal candidate combines deep AI/ML expertise with strong software data cloud and enterprise architecture experience and has demonstrated success guiding complex technology solutions from concept through production. A key focus of this role will be identifying common needs across RTX business units and translating them into reusable enterprise AI capabilities reference architectures and design patterns that accelerate adoption while reducing duplication and technical complexity.

What You Will Do

• Define end-to-end architectures for enterprise AI and ML solutions spanning traditional machine learning Generative AI agentic AI data applications APIs platforms infrastructure and enterprise systems.

• Partner with business and technology leaders to translate business opportunities and requirements into architecture blueprints technical strategies success criteria and implementation roadmaps.

• Determine the appropriate technical approach for complex business problems including traditional software machine learning Generative AI retrieval-augmented generation agentic AI or combinations of these approaches.

• Develop reusable reference architectures design patterns standards and technical guardrails and identify common requirements across RTX business units that can be addressed through reusable enterprise AI capabilities.

• Architect modern AI solutions including model selection and routing retrieval and grounding context engineering agent orchestration tool use state and memory human-in-the-loop workflows evaluation observability and secure enterprise integration.

• Define architecture patterns for AI/ML data pipelines model serving model lifecycle management MLOps deployment monitoring and operation across cloud hybrid on-premises and restricted environments.

• Evaluate technology and platform alternatives and lead build buy configure and integrate decisions considering business value scalability interoperability security performance cost and operational complexity.

• Lead architecture and technical design reviews partner with enterprise architecture cybersecurity data identity privacy and Responsible AI teams and provide technical leadership and mentorship across engineering teams.

What You Will Learn

• How AI and ML technologies are applied across a global aerospace and defense enterprise spanning diverse business engineering manufacturing and operational domains.

• How enterprise AI platforms and reusable architecture patterns enable AI solutions to scale across multiple business units while meeting security data and governance requirements.

• How Generative AI and agentic AI capabilities are evolving from experimentation into production systems that interact with enterprise data tools applications and workflows.

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

• How emerging AI technologies models frameworks interoperability standards and industry practices can be evaluated and translated into practical enterprise capabilities.

• How to influence the technical direction of enterprise AI by working across business units architecture disciplines engineering organizations and senior leadership.

Qualifications You Must Have

• A University Degree in Computer Science Artificial Intelligence Machine Learning Engineering or a related STEM discipline and a minimum of 10 years of relevant professional experience or an Advanced Degree in a related field and a minimum of 7 years of relevant professional experience.

• A minimum of 5 years of experience designing developing integrating or architecting AI/ML solutions including experience taking AI or ML capabilities beyond experimentation into production environments.

• Experience serving as a technical architect solution architect technical lead or senior engineer for complex enterprise software data cloud or AI/ML systems.

• Technical experience with AI/ML systems and modern AI application architectures including Generative AI and large language models.

• Experience designing distributed systems APIs microservices enterprise integrations data pipelines or cloud-native applications using at least one major public cloud platform.

• Experience translating business and technical requirements into architecture designs and evaluating technical business cost security and operational tradeoffs.

• Experience working with enterprise security concepts including identity and access management authentication and authorization data protection application security and secure system integration.

Qualifications We Prefer

• Experience architecting production Generative AI retrieval-augmented generation agentic AI or multi-agent systems including modern AI architecture patterns including model selection and routing embeddings vector and enterprise search context engineering structured outputs tool calling orchestration memory state and human-in-the-loop workflows.

• Experience with emerging agent technologies and interoperability approaches such as Model Context Protocol (MCP) agent identity secure tool integration or similar standards.

• Experience with AI evaluation observability tracing guardrails model monitoring Responsible AI model governance or production AI reliability and with traditional machine learning lifecycle capabilities including data pipelines feature engineering model serving model registries monitoring and MLOps.

• Experience designing AI architectures across multiple models vendors platforms and cloud hybrid on-premises or restricted environments.

• Experience with Kubernetes containers CI/CD infrastructure-as-code and modern application deployment architectures.

• Familiarity with relevant AI risk cloud architecture and enterprise architecture frameworks and principles such as NIST AI RMF cloud well-architected frameworks TOGAF Zachman or similar disciplines and experience applying them to enterprise technology decisions.

• Demonstrated ability to lead technical discussions influence architecture decisions across multidisciplinary teams and communicate complex technical concepts to technical and non-technical stakeholders.

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 132400 USD - 251600 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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