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DevOps Engineer (Automation Systems)(m/w/x)
Designing and deploying infrastructure for automation workflows at AI project connector. 3+ years DevOps experience required. Performance-based bonus programs.
Requirements
- 3+ years of DevOps, infrastructure engineering, or backend system management experience
- Bachelor's or Master’s Degree in Computer Science, Engineering, or related technical fields
- Strong cloud platforms, server environments, and deployment workflows experience
- Ability to maintain high-availability systems and scalable architectures
- Experience setting up monitoring, logging, and alerting systems
- Familiarity with containerization tools (Docker or similar)
- Understanding of system performance, scaling strategies, and fault tolerance
- Experience supporting automation platforms and high-frequency workflows
- Strong attention to detail and commitment to system reliability
- Self-directed work ethic with independent troubleshooting and optimization ability
- Portfolio or examples demonstrating infrastructure setup, monitoring, or scaling systems
- English proficiency: Upper-intermediate (B2) or above
Tasks
- Collaborate with Tendem Agents on repetitive tasks
- Provide infrastructure expertise and system reliability
- Optimize performance for stable and scalable automation pipelines
- Design and deploy infrastructure for automation workflows
- Maintain self-hosted automation environments
- Support high-volume workflows and large-scale data processing
- Scale automation systems for concurrent workloads
- Set up monitoring and logging systems
- Track workflow performance and detect failures
- Implement alerts for critical events
- Ensure system uptime and fault tolerance
Work Experience
- 3 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- DevOps
- Docker
Benefits
Bonuses & Incentives
- Performance-based bonus programs
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DevOps Engineer (Automation Systems)(m/w/x)
Designing and deploying infrastructure for automation workflows at AI project connector. 3+ years DevOps experience required. Performance-based bonus programs.
Requirements
- 3+ years of DevOps, infrastructure engineering, or backend system management experience
- Bachelor's or Master’s Degree in Computer Science, Engineering, or related technical fields
- Strong cloud platforms, server environments, and deployment workflows experience
- Ability to maintain high-availability systems and scalable architectures
- Experience setting up monitoring, logging, and alerting systems
- Familiarity with containerization tools (Docker or similar)
- Understanding of system performance, scaling strategies, and fault tolerance
- Experience supporting automation platforms and high-frequency workflows
- Strong attention to detail and commitment to system reliability
- Self-directed work ethic with independent troubleshooting and optimization ability
- Portfolio or examples demonstrating infrastructure setup, monitoring, or scaling systems
- English proficiency: Upper-intermediate (B2) or above
Tasks
- Collaborate with Tendem Agents on repetitive tasks
- Provide infrastructure expertise and system reliability
- Optimize performance for stable and scalable automation pipelines
- Design and deploy infrastructure for automation workflows
- Maintain self-hosted automation environments
- Support high-volume workflows and large-scale data processing
- Scale automation systems for concurrent workloads
- Set up monitoring and logging systems
- Track workflow performance and detect failures
- Implement alerts for critical events
- Ensure system uptime and fault tolerance
Work Experience
- 3 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- DevOps
- Docker
Benefits
Bonuses & Incentives
- Performance-based bonus programs
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Mindrift
Industry
IT
Description
Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.
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