AI Solution Architect (hybrid)

RTX RTX · Aerospace · charlotte, NC +4 · Digital Technology

AI Solution Architect for RTX, responsible for guiding internal business customers in the evaluation and implementation of AI-enabled Enterprise AI solutions. This role involves assessing use cases, recommending existing platforms or vendor solutions, consulting on AI initiatives, and ensuring adherence to Responsible AI, Cybersecurity, Legal, and Privacy policies. The architect will also drive enterprise alignment to prevent duplication and promote reuse of AI platforms.

What you'd actually do

  1. Partner with internal business customers across Collins strategic business units and central functions to understand AI use case requirements, assess feasibility, and translate business needs into solution options with clearly articulated tradeoffs.
  2. Assess commercially available vendor AI tools, platforms, and services as candidate solutions; conduct structured capability evaluations including technical fit, security posture, integration complexity, data governance implications, cost modeling, and vendor viability.
  3. Apply RTX's Responsible AI framework to evaluate proposed use cases and solutions, identifying risks related to bias, fairness, transparency, explainability, human oversight, and data privacy.
  4. Drive alignment of proposed AI initiatives with enterprise AI strategies, architecture standards, and technology roadmaps to avoid proliferation of overlapping capabilities and fragmented investments.
  5. Communicate complex technical concepts, tradeoffs, and risk findings clearly to audiences including senior leadership, program managers, engineers, and non-technical business stakeholders.

Skills

Required

  • University Degree and minimum 10 years prior relevant experience or an Advanced Degree in a related field and minimum 7 years of experience
  • U.S. Citizenship is required
  • Familiarity with enterprise AI/ML architecture patterns, including generative AI, large language models (LLMs), retrieval-augmented generation (RAG), ML pipelines, and model governance.
  • Experience working across multiple business functions or programs as a technical advisor, solutions architect, or enterprise architect with a track record of translating business requirements into actionable technical recommendations.
  • Demonstrated knowledge of AI risk, ethics, and responsible AI principles, including experience applying governance frameworks in a practical decision-making context.
  • Strong written and verbal communication skills with a proven ability to synthesize complex technical information into clear, concise recommendations for senior stakeholders.

Nice to have

  • Experience in an Aerospace and Defense or regulated government contracting environment, with familiarity with export control (EAR/ITAR), data classification, and program security requirements as they relate to AI systems.
  • Knowledge of the NIST AI Risk Management Framework (AI RMF), DoD AI Ethics Principles, or equivalent responsible AI frameworks.
  • Hands-on experience building, deploying, or operating AI/ML solutions, including working with cloud AI services (Azure AI, AWS Bedrock, Google Vertex AI) and enterprise AI platforms.
  • Experience evaluating AI vendor statements of work, capability roadmaps, and AI transparency documentation; familiarity with SaaS/AI contractual risk provisions.
  • Understanding of enterprise architecture governance processes and technology portfolio management, including experience contributing to an architecture review board or similar governance body.
  • Advanced degree (M.S. or Ph.D.) in Computer Science, Artificial Intelligence, Systems Engineering, Data Science, or a related t

What the JD emphasized

  • U.S. citizenship is required
  • Active and existing security clearance required after day 1
  • Responsible AI framework
  • Responsible AI
  • risk

Other signals

  • evaluating AI solutions
  • responsible AI framework
  • enterprise AI strategy