DevOps Engineer (Automation Systems) - Freelance AI Trainer
United StatesContractMiddle
SalaryAt least 60 USD per hour
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Job Details
- Languages
- English
- Experience
- Minimum 3+ years
- Required Skills
- Docker
Requirements
- Minimum 3+ years of experience in DevOps, infrastructure engineering, or backend systems management.
- Strong experience with cloud platforms, server environments, and deployment pipelines.
- Proven ability to design and maintain high-availability and scalable systems.
- Hands-on experience with monitoring, logging, and alerting tools (metrics, logs, uptime monitoring).
- Familiarity with containerization tools such as Docker or equivalent technologies.
- Solid understanding of system performance optimization, scaling strategies, and fault tolerance principles.
- Experience supporting automation platforms or high-frequency workflow systems.
- Strong troubleshooting skills with the ability to work independently in complex environments.
- High attention to detail and strong focus on system reliability and stability.
- Ability to manage infrastructure in remote and self-directed work environments.
- Upper-intermediate or higher English proficiency (B2+ required).
Responsibilities
- Deploy, configure, and maintain self-hosted automation environments such as n8n or similar workflow systems.
- Design and manage scalable infrastructure to support high-volume automation workflows and data processing tasks.
- Ensure system reliability, uptime, and fault tolerance across distributed automation pipelines.
- Implement and maintain monitoring, logging, and alerting systems to track performance and detect failures.
- Set up alerts for critical system events such as node failures, performance degradation, or workflow disruptions.
- Optimize infrastructure to handle concurrent workloads and performance-intensive operations.
- Support scaling strategies to ensure systems remain stable under increasing demand.
- Troubleshoot infrastructure issues and independently resolve system-level performance problems.
- Continuously improve deployment workflows and automation reliability.
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