AI Platform Engineer (Hybrid)

We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills?, Benefits, Pay, Schedule. Only include sections that have real specific content. We must not repeat job title. Must not include Job ID etc. Must remove boilerplate like EEO, legal, application instructions, etc. We need to parse the posting. Key sections: - About the role: The paragraph after "At RTX, the world's largest aerospace..." up to "Join us and help shape the future of aerospace and defense." Also maybe the description of the position: "The following position is to join our RTX Enterprise Services team: We are seeking an experienced AI Platform Engineer..." That could be part of About the role. - Responsibilities: The bullet list under "What You Will Do". That's a list of duties. - Requirements: The "U.S. Citizen, U.S. Person, or Immigration Status Requirements:" paragraph about U.S. Person definition and link. Also maybe "Security Clearance Type: None/Not Required" etc. But we should include only substantive content. The U.S. Person requirement is a requirement. Also maybe "Work Location: This is a hybrid role, eligible candidates must reside within commuting distance of ..." That's more about schedule/location, maybe schedule? But schedule section only if specific schedule given. There's no explicit schedule like "Monday-Friday 9-5". So we may not include Schedule. - Qualifications: The "Qualifications You Must Have" and "Qualifications We Prefer". Those are qualifications. - Skills: Not explicitly listed separate; maybe we could combine skills under Qualifications? But we could create a Skills section if there is explicit list of skills. The posting includes programming languages, experience with Docker, Kubernetes, etc. Those are qualifications/skills. Could create a Skills section summarizing technical skills. However instruction: Prefer a few substantive sections over many thin ones. Could combine Skills into Qualifications. But we have separate Qualifications section already. Might not need Skills. - Benefits: The "What We Offer" paragraph describing total rewards package, list of benefits: parental leave, flexible work schedules, achievement awards, educational assistance, child/adult backup care, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, employee assistance program, Employee Scholar Program, parental leave, paid time off, holidays, annual short-term and/or long-term incentive compensation programs. That's benefits. - Pay: The salary range: "The salary range for this role is 107,500 USD - 204,500 USD." Also mention that it's a good faith estimate. So we can include Pay section. - Schedule: Not given specific schedule; only hybrid role description. Could we treat hybrid as schedule? The instruction: include Schedule section only if posting actually states them. It does state hybrid role and ratio of time working onsite determined in partnership with leader. That's somewhat schedule info. Might be considered schedule. But it's vague. Might be better to omit Schedule because not specific like "Monday-Friday". However the instruction says "never create Pay/Schedule/Benefits sections unless the posting actually states them." It does state hybrid role and that ratio determined with leader. That's a statement about schedule. So we could include Schedule with that info. But we also have Work Location: list of cities. That's location not schedule. Could be part of About the role or maybe a separate Location section but not requested. We'll ignore. We must not include boilerplate like EEO, privacy policy, etc. We need to preserve all substantive information; do not invent or summarize away detail. So we need to keep the details. We'll produce HTML with headings

for each section. We'll use

• for lists. We'll use

  for prose. We must not repeat job title as heading. We'll not include markdown fences. Let's craft. Sections:

  About the role

  At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world’s 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.

  Responsibilities

  • 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.

  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: https://www.ecfr.gov/current/title-22/chapter-I/subchapter-M/part-120/subpart-C/section-120.62

  Security Clearance Type: None/Not Required

  Security Clearance Status: Not Required

  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.

  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.

  Benefits

  Whether you’re 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.

  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.

  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 company’s performance.

  Pay

  The salary range for this role is 107,500 USD - 204,500 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 candidate’s work experience, location, education/training, and key skills.

  Schedule

  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