RTX-posted about 2 months ago
Full-time • Mid Level
Remote • Hartford, CT
5,001-10,000 employees

As an AI Cloud Engineer at Raytheon Technologies, you will lead the design, deployment, and optimization of scalable AI and machine learning solutions on cloud platforms. This role involves leveraging best-in-class cloud technologies to build and maintain infrastructure that powers advanced AI models and analytics capabilities. You will collaborate with cross-functional teams to ensure seamless integration of AI solutions into the enterprise ecosystem, driving innovation and supporting RTX’s mission to protect and connect the world.

  • Architect, implement, and manage cloud-based solutions to support AI and machine learning workloads across platforms such as Azure, AWS, or GCP.
  • Optimize cloud resources for scalability, performance, and cost-efficiency while ensuring robust security and compliance measures.
  • Collaborate with data scientists and engineers to deploy machine learning models in production and maintain MLOps pipelines for training, testing, deployment, and monitoring.
  • Utilize cloud-native tools and services like Azure Machine Learning, AWS SageMaker to deliver AI solutions.
  • Leverage containerization (Docker) and orchestration (Kubernetes) technologies for efficient deployment and scaling of AI solutions.
  • Work closely with cross-functional teams, including Data Engineering, Architecture, and Security, to align cloud strategies with organizational goals.
  • Monitor and manage cloud infrastructure to maintain reliability, performance, and security while driving cost optimization initiatives, and adhering to RTX policy updates.
  • Explore and implement emerging technologies in AI, cloud computing, and generative AI frameworks, such as LLMs and RAG, to enhance RTX’s AI capabilities.
  • Provide technical guidance and engage stakeholders to gather requirements, deliver impactful results, and recommend innovative cloud-based AI solutions.
  • Bachelor’s degree in Computer Science, Engineering, or a related field and 10+ years of experience in cloud engineering or AI/ML solution development.
  • Certification in AWS or Azure and their AI/ML services.
  • Strong understanding of MLOps principles and tools.
  • Experience with containerization (Docker) and orchestration (Kubernetes).
  • Proficiency in programming languages such as Python, Java, or C++.
  • Master’s degree in a relevant field.
  • Experience with generative & agentic AI technologies and frameworks.
  • Familiarity with infrastructure-as-code tools such as Terraform or CloudFormation.
  • SAFe devops or similar certification
  • Additional soft skills: communication, problem-solving &collaboration.
  • 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.
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