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About This Role
Date Posted:
2026\-08\-11Country:
United States of America
Location:
US\-NC\-CHARLOTTE\-2730 \~ 2730 W Tyvola Rd \~ TYVOLA
Position Role Type:
Hybrid
U.S. Citizen, U.S. Person, or Immigration Status Requirements:
U.S. citizenship is required, as only U.S. citizens are authorized to access information under this program/contract.
Security Clearance Type:
None/Not Required
Security Clearance Status:
Not Required
Collins Aerospace is a leader in technologically advanced, intelligent solutions that help redefine the aerospace and defense industry. With a comprehensive portfolio and deep technical expertise, we help customers meet the demands of the global market. Join us and help shape the future of aerospace and defense.
Collins Aerospace is seeking an experienced and forward\-thinking AI/ML architect to be part of our Data and Artificial Intelligence (AI) Solutions organization. This role is responsible for translating business requirements into AI architecture blueprints, success metrics, and roadmaps. In this role, you will partner with AI leaders and implementors across Collins and RTX to strategically align on capability delivery and lead the end\-to\-end architecture of AI and Machine learning (ML) solutions across the Collins landscape. This role bridges business strategy, data science and engineering to design scalable, secure, and production\-ready
AI/ML solutions that drive measurable business value.
If you are passionate about AI/ML architecture and have expertise in incorporating them with an extended ecosystem of business\-critical applications, we invite you to apply and contribute to transformative initiatives within our global organization.
*\*\ *This is a hybrid\-based position at one of Collins’ major facilities. \*\****
What YOU will do:
*Strategy \& Architecture*
- Define Collins AI/ML architecture aligned with Business goals and digital strategy
- Establish reference architectures, design patterns and standards for AI/ML solutions.
Lead the adoption of modern AI capabilities (e.g. Generative AI, Deep Learning, NLP, RAG).
- Collaborate with Domain Architects in Security, Infrastructure, Data \& Business unit, to refine and evolve the Solution architectures, processes, practices, leveraging architectural frameworks (e.g. TOGAF, Zachman, DODAF, etc.).
*Solution Design \& Delivery*
- Architect end\-to\-end AI/ML solutions (data ingestion, feature engineering, model development, deployment, monitoring) for business use cases.
- Partner with AI teams, Data Scientists and Engineers to operationalize models.
- Ensure scalability, reliability, and performance of AI systems in production.
*Data \& Platform Architecture*
- Define architecture for data pipelines and feature stores to support ML workloads.
- Ensure integration with enterprise data ecosystems and APIs.
*Governance, Risk \& Ethics.*
- Establish AI governance frameworks (model validation, explain ability, bias detection).
- Ensure compliance with security, privacy, and regulatory requirements.
- Promote responsible and ethical AI practices.
*Technology Leadership*
- Stay current with emerging trends (LLMs, Vector databases, etc.)
- Provide technical leadership and mentorship to teams.
*Stakeholder Engagement*
- Collaborate with business leaders to identify AI opportunities.
- Translate business requirements into technical solutions.
- Communicate architecture decisions to executive and technical stakeholders.
Qualifications YOU Must Have:
- Typically requires a University Degree and minimum 12 years prior relevant experience or an Advanced Degree,
- U.S. Citizen \- U.S. citizenship is required, as only U.S. citizens are authorized to access information under this program/contract.
- 8\+ years of broad\-based experience in Data and AL/ML architecture, deployments, integration, or consulting, with extensive experience in implementing AI/ML Solutions for large complex organizations.
- In\-depth knowledge of AI/ML frameworks. Expertise in data architecture, distributed systems and APIs. Experience with CI/CD for ML, Model monitoring, and versioning (MLOps).
- Proven track record as a Solution Architect or Technical Lead, crafting new solutions and delivering business outcomes.
Qualifications We Prefer:
- Experience with Generative AI/ Large language Models (LLMs). Knowledge of vector databases, embeddings and prompt engineering.
- Familiarity with data and AI/ML concepts and technologies.
- Strong understanding of AI ethics, governance and regulatory frameworks.
- Relevant experience in Aerospace \& Defense industry preferred. Familiarity with the unique needs of manufacturing and aerospace, including compliance, quality management, and traceability.
- Experience with working on enterprise architecture frameworks (TOGAF, Zachman, DoDAF) \& tools (SparxEA, Cameo, LeanIX). Certification in any of the framework’s a plus.
- Experience with Agile methodology such as Scaled Agile Framework (SAFe) and tools such as Jira.
- Exceptional interpersonal, collaboration, and communication skills, with an ability to convey complex technical concepts to non\-technical stakeholders.
- Ability to balance innovation with pragmatic delivery. Lead and influence without authority.
- Demonstrated experience in guiding cross\-functional teams and fostering alignment on architecture strategies across stakeholders.
What We Offer:
Some of our competitive benefits packages include:
- Medical, dental, and vision insurance.
- Three weeks of vacation for newly hired employees.
- Generous 401(k) plan that includes employer matching funds and separate. employer retirement contribution, including a Lifetime Income Strategy option.
- Tuition reimbursement program.
- Student Loan Repayment Program.
- Life insurance and disability coverage.
- Optional coverages you can buy pet insurance, home and auto insurance, additional life and accident insurance, critical illness insurance, group legal, ID theft protection.
- Birth, adoption, parental leave benefits.
- Ovia Health, fertility, and family planning.
- Adoption Assistance.
- Autism Benefit.
- Employee Assistance Plan, including up to 10 free counseling sessions.
- Healthy You Incentives, wellness rewards program.
- Doctor on Demand, virtual doctor visits.
- Bright Horizons, child, and elder care services.
- Teladoc Medical Experts, second opinion program.
- And more!
Learn More \& Apply Now!
Do you want to be part of a new, exciting initiative to combine foundational IT with new digital technologies? Our Digital Technology team is driving business efficiencies and a better customer experience by connecting technologies, people, information and processes. From making aircraft more electric, intelligent and integrated to building new software platforms such as Internet of Things, big data, artificial intelligence, and blockchain, there’s no better place to be right now than in digital. If you’re an agile thinker who enjoys utilizing modern technology to make big improvements, then you’re a perfect fit for this team. Join Collins Aerospace to help us revolutionize the aerospace industry today!
WE ARE REDEFINING AEROSPACE.
- Please consider the following role type definitions as you apply for this role.
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.
*Regardless of your role type, collaboration and innovation are critical to our business and all employees will have access to digital tools so they can work with colleagues around the world – and access to Collins sites when their work requires in\-person meetings.*
At Collins, the paths we pave together lead to limitless possibility. And the bonds we form – with our customers and with each other \- propel us all higher, again and again.
Apply now and be part of the team that’s redefining aerospace, every day.
*As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select 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 157,200 USD \- 298,800 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.
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 company’s 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.*
Privacy Policy and Terms:
Salary Context
This $157K-$298K range is above the 75th percentile for AI Architect roles in our dataset (median: $181K across 29 roles with salary data).
Role Details
About This Role
This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.
The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.
Across the 4,317 AI roles we're tracking, AI Architect positions make up 1% of the market. At Collins Aerospace, this role fits into their broader AI and engineering organization.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
What the Work Looks Like
Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
Skills Required
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.
Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
Compensation Benchmarks
AI Architect roles pay a median of $237,300 based on 102 positions with disclosed compensation. Director-level AI roles across all categories have a median of $274,554. Disclosed range: $157K to $298K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Collins Aerospace AI Hiring
Collins Aerospace has 3 open AI roles right now. They're hiring across AI Architect, AI Software Engineer, AI/ML Engineer. Positions span Charlotte, NC, US, Cedar Rapids, IA, US. Compensation range: $204K - $298K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI Architect roles include Software Engineer, Data Scientist, Data Analyst.
From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.
Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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