Junior Cloud Platform Engineer
4 weeks ago
Job DescriptionJunior Cloud Platform Engineer
- Remote Job, 1+ Year Experience
Annual Income:
$60K - $65K, Onsite
A valid work permit is necessary in the US/Canada
About us:
Patterned Learning is a platform that aims to help developers code faster and more efficiently. It offers features such as collaborative coding, real-time multiplayer editing, and the ability to build, test, and deploy directly from the browser. The platform also provides tightly integrated code generation, editing, and output capabilities.
About the job
Responsibilities
Assist in the execution of DevOps tasks for the client's cloud environment, including code migration and deployment processes in the AWS cloud environment.Collaborate with senior engineers to monitor AWS resources and ensure optimal performance and reliability of the client environment.Participate in maintenance activities for the client environment, including patching, upgrades, and troubleshooting.Provide support for environment configuration, including setting up infrastructure as code and ensuring consistency across environments.Assist in the implementation and maintenance of application monitoring solutions to ensure the health and performance of the client's application.Contribute to application software support activities, including troubleshooting and resolving issues related to the client's application.Skill Requirements
Basic understanding of application monitoring concepts and tools.Familiarity with providing application software support and troubleshooting.Knowledge of DevOps principles and practices.Bachelor's Degree in Computer Science, Information Technology, or a related field.
Why Patterned Learning LLC?
Patterned Learning can provide intelligent suggestions, automate repetitive tasks, and assist developers in writing code more effectively. This can help reduce coding errors, improve productivity, and accelerate the development process.
The pattern recognition is particularly relevant in the context of coding. Neural networks, especially deep learning models, are commonly employed for pattern detection and classification tasks. These models simulate human decision-making and can identify patterns in data, making them well-suited for tasks like code analysis and generation.
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