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We are seeking a skilled and dedicated DevOps Engineer to join our team. The successful candidate will be responsible for automating deployment processes, managing cloud infrastructure, and ensuring the scalability and reliability of our GenAI applications. This role is crucial in maintaining the efficiency and effectiveness of our innovative AI solutions
Job Responsibility:
Design, implement, and manage scalable, secure, and reliable cloud infrastructure on AWS and Azure to support GenAI applications
Automate deployment, monitoring, and management processes for GenAI applications to ensure high availability and performance
Collaborate with development teams to streamline CI/CD pipelines using tools such as GitHub Actions, enabling rapid and reliable deployment of new features and updates
Optimize cloud resources to ensure cost-effectiveness while maintaining performance and scalability
Implement and manage infrastructure as code (IaC) using tools such as Terraform, CloudFormation, or ARM templates
Deploy and manage containerized applications using Amazon ECS and Kubernetes
Monitor system performance, troubleshoot issues, and implement solutions to prevent downtime and data loss
Ensure compliance with security best practices and policies across all cloud environments
Maintain and enhance GenAI applications on Retrieval-Augmented Generation (RAG) and Agentic platforms, ensuring they meet business requirements and performance standards
Collaborate with cross-functional teams to identify and implement improvements in system architecture and processes
Stay updated with the latest industry trends and technologies to continuously improve our infrastructure and processes
Requirements:
Bachelor's degree in Computer Science, Information Technology, or a related field
Proven experience as a DevOps Engineer, preferably with Gen AI applications
Strong knowledge of Infrastructure as Code (IaC) tools
Proficiency in CI/CD methodologies and tools
Experience with cloud services such as AWS and Azure
Excellent problem-solving skills and attention to detail
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