DevOps Infrastructure Engineer
Key values
B2B
Contract
Remote, Czechia
Location
ASAP
Start
+12 months
Length
Requirements
CI/CD
GitLab
Linux
Docker
Jenkins
Ansible
Python
Terraform
Description
This recruitment process is project-based oriented – it means that after receiving an offer from EndySoft, you will be assigned to work in one specific project for one of our Czech clients from IT sector.
MD rate: 160 – 200 EUR
Key Responsibilities:
- Develop and Support DevOps Infrastructure: Implement and maintain infrastructure to support automation, CI/CD flows, tools integration, testing, deployment, and scalability for Cloud RAN.
- CI/CD Pipeline Management: Provide support for CI/CD pipeline services, ensuring smooth operation for development and testing teams.
- Tools Integration: Manage integration of development and testing tools into the CI/CD pipeline, ensuring efficient workflows for software releases.
- Automation and Testing: Develop automated test cases and processes for continuous integration and deployment, ensuring code quality and system reliability.
- Infrastructure Scalability and Monitoring: Implement infrastructure that can scale with the increasing needs of the teams, and monitor performance, data collection, and services.
- Data Management and Visualization: Support data management and create visualizations that help teams understand the performance of their pipelines and services.
- Support for Test Channels: Collaborate with sister organizations to support the building of test labs and test tools, ensuring that testing environments are properly integrated into the CI/CD process.
- Machine Learning and AI Integration: Explore and integrate machine learning and AI tools to optimize pipeline processes and decision-making.
Required Skills:
- Strong experience in CI/CD pipelines and DevOps infrastructure development.
- Programming skills: Python, Java, and C++.
- Experience with automation frameworks and developing automated test cases.
- Familiarity with RAN (Radio Access Networks) is a plus.
- Proficiency in integrating and managing tools used in software development and testing.
- Knowledge of machine learning and AI tools is a plus.
- Strong understanding of cloud infrastructure scalability and monitoring solutions.