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Primary Job Responsibilities
Set up and maintain automated build systems; ensure that code can be compiled and built into deployable artifacts with minimal manual intervention.
Manage deployment of software releases to various environments (e.g., development, staging, production); this may involve creating scripts and using deployment tools to automate and streamline the deployment process.
Oversee versioning of software releases, ensuring that different versions of the software are correctly tagged and documented in version control systems.
Integrate various components of the software system, including third-party tools and libraries; ensure system components work together seamlessly.
Partner closely with quality engineers to ensure that automated tests are run as part of the build and deployment process. They may also be involved in setting up continuous integration/continuous deployment (CI/CD) pipelines.
Actively monitor the deployment and operation of software in production environments, troubleshoot issues that arise, and work on resolution strategies.
Document release procedures, configurations, and deployment processes to ensure that there is clear, reproducible guidance for future releases.
Collaborate with developers, quality engineers, and operations teams to ensure that software releases are aligned to expected timetables and meet production standards.
Contribute to the development of the open-source projects that comprise Red Hat’s AI family of products.
Regularly communicate with project stakeholders including other teams of Red Hat engineers, product managers, consultants, management, and senior leadership.
Required Skills
5+ years of experience as a software developer, software engineer, or similar roles.
Extensive experience developing in Python. Experience with Go and C/C++ languages are not required, but are considered nice to have.
Experience creating automation for GitHub, using GitHub actions or related continuous integration tools.
Experience developing functional and non-functional testing.
Experience working with production level environments and containers, troubleshooting issues, and working with YAML.
Proficiency with build automation tools (e.g., Jenkins, GitLab CI/CD, Travis CI).
Strong documentation skills to create clear, comprehensive release notes, procedures, and configuration guidelines.
Ability to quickly learn and use new tools and technologies.
Nice to Haves
Experience writing Kubernetes controllers and operators.
Experience with deployment tools and orchestration systems (e.g., Docker, Kubernetes, Helm).
Familiarity with AI and Machine Learning platforms, tools, and frameworks, such as: Tensorflow, PyTorch, LLaMA.cpp, and Kubeflow.
Experience creating Ansible automation scripts.
Experience with hardware accelerators, such as GPU, CUDA, and ROCm.
Understanding of DevOps methodology.
Bachelor's degree or higher in computer science or other related discipline.
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