AI Automations Cloud Deployment Engineer

October 31

🦌 Connecticut – Remote

Although this job is listed in Connecticut, this company may be open to hiring remote in other states.

💵 $124k - $250k / year

⏰ Full Time

🟠 Senior

🔴 Lead

⛑ DevOps & Site Reliability Engineer (SRE)

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RTX

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Aerospace • Defense • Sustainability

RTX is a globally recognized aerospace and defense company dedicated to transformative technologies and era-defining innovation. It operates through various businesses, including Collins Aerospace, Pratt & Whitney, and Raytheon, with a focus on sustainable, connected flight and smarter defense systems. RTX is committed to diversity, equity, and inclusion across the company and aims to solve the world’s most complex problems with cutting-edge technology and talent. Additionally, RTX is involved in significant projects like upgrading the F135 Engine Core and developing missile-defense systems. The company emphasizes corporate responsibility and sustainable practices.

10,000+ employees

Founded 2020

🚀 Aerospace

📋 Description

• 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. • Monitor and manage cloud infrastructure to maintain reliability, performance, and security while driving cost optimization initiatives.

🎯 Requirements

• 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++.

🏖️ Benefits

• Health insurance • Medical, dental, and vision insurance • Retirement plans • Paid time off • Parental leave • Flexible work schedules • Achievement awards • Educational assistance • Child/adult backup care