AI Architect (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 content. We need to parse the posting. First, remove boilerplate: Date Posted, Country, Location, Position Role Type, U.S. Citizen etc, Security Clearance, etc. Also remove "Learn More & Apply Now!" and application instructions, EEO, privacy policy, etc. We need to keep substantive info: At RTX description, The following position is to join our RTX Enterprise Services team: We are seeking an experienced AI Architect... That's about the role. Then "What You Will Do" list of duties. Then "What You Will Learn" maybe could be part of Responsibilities or maybe a separate section like "What You Will Learn" but not in allowed headings. Allowed headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Skills, Benefits, Pay, Schedule. So we need to map content. "About the role": likely the introductory paragraph describing the role and team. "Responsibilities": the bullet list under "What You Will Do". "Requirements": maybe the citizenship/immigration requirement? Actually that is a requirement: "U.S. Person". Also security clearance none. Could be placed under Requirements. "Qualifications": the "Qualifications You Must Have" and "Qualifications We Prefer". Could combine. "Skills": maybe we could extract technical skills from qualifications? But we have qualifications already; maybe we can put skills under Qualifications? The instruction says we can have Skills section if there is real content. We could list skills like AI/ML, cloud, etc. But we already have qualifications; maybe better to put skills under Qualifications. However we need to decide. "Benefits": The "What We Offer" paragraph includes benefits. Also later mentions specific 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. Also incentive compensation. So we can create Benefits section. "Pay": The salary range: 132,400 USD - 251,600 USD. "Schedule": Hybrid role description: work location hybrid, eligible candidates must reside within commuting distance of list of cities. Also description of hybrid: Employees who are working in Hybrid roles will work regularly both onsite and offsite. Ratio determined with leader. Also mention may be asked to attend interview steps in-person. That's schedule info. Thus we will create sections: About the role, Responsibilities, Requirements, Qualifications, Benefits, Pay, Schedule. We may also include Skills if we want but not needed. We must not repeat job title as heading. No Job ID. We must not include filler like "commensurate with experience". Not present. We must preserve all substantive information; do not invent or summarize away detail. So we need to keep details like list of cities for hybrid, etc. We need to format using

for headings,

• for lists,

  for prose. We need to ensure we don't include boilerplate like EEO, privacy policy, etc. Let's extract content. About the role: The paragraph after "The following position is to join our RTX Enterprise Services team:" plus maybe the preceding sentence about RTX description? The posting includes: "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 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." That seems appropriate for About the role. Responsibilities: The bullet list under "What You Will Do". Let's capture each sentence as a list item. List: - 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. We could also include "What You Will Learn" maybe as part of Responsibilities? But it's more about learning outcomes. Could be placed under Responsibilities as additional bullet points? However the instruction says we should not create sections with filler. "What You Will Learn" is substantive; we could incorporate as part of Responsibilities or maybe as a separate section like "What You Will Learn" but not allowed heading. So we could add those as bullet points under Responsibilities as well, but they are about learning not doing. Might be okay to include them under Responsibilities as they are still part of role description. But better to keep them separate? The allowed headings do not include a "Learning" section. So we could incorporate them into About the role or Responsibilities. I think we can add them as bullet points under Responsibilities as they describe what the candidate will learn/experience. It's still part of role. Thus we add bullet points: - 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. Now Requirements: The U.S. Person requirement and maybe security clearance none. Also maybe "U.S. Citizen, U.S. Person, or Immigration Status Requirements: This job requires a U.S. Person." Also mention that U.S. citizens, nationals, permanent residents, refugees, asylees are considered U.S. persons. Also link to definition. We can include that as prose. We could also mention that security clearance type: None/Not Required, status: Not Required. That's also a requirement. Thus Requirements section: a paragraph summarizing. Qualifications: Must Have and Preferred. We need to list them as bullet points under Qualifications. 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. Preferred: - 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. We could also include "Skills" section extracting technical skills like AI/ML, cloud, etc. But we already have qualifications; maybe we can omit Skills. Benefits: The "What We Offer" paragraph plus later specifics. Let's extract: - 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. - Learn More & Apply Now! (remove) - Later: 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