

Qualified candidates will be comfortable participating in discussions and decisions around technical design and architecture, release planning, automated testing, and productization. This job role is integral to ensuring that new features, bug fixes, and updates are delivered efficiently and reliably to end-users.
What you will do:
Collaborate with Staff Engineers, Engineering, Product Management, and User Experience to understand customer needs and use cases.
Apply technology background in software engineering and systems engineering to make contributions to a Python-based midstream automation platform in the areas of CI/CD, observability, and continuous testing.
Execute manual and automated tests for Red Hat AI midstream project/components and deliver clear status updates in a timely manner.
Explore, identify, and document unwanted behavior, output, and bias in Red Hat AI models. Advocate for the resolution of critical issues and communicate the impact on customers to the development team(s).
Monitor and participate in upstream AI/ML communities, evaluating new AI/ML-related technologies in the space and considering potential integrations and collaborations upstream.
Conduct new feature research and design test cases with emphasis on model performance, scalability, automation, and bias reduction.
Lead or contribute to technical initiatives that grow, improve, and scale our existing processes.
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.
What you will bring:
Advanced Linux administration skills, including containers
Advanced Python development and troubleshooting skills
Experienced with writing and reading Shell scripts (e.g. bash)
Experienced in building and maintaining delivery pipelines and workflows with GitLab CI, GitHub Actions, or comparable technologies
Ability to quickly learn and use new tools and technologies.
Understanding of DevOps methodology
The following will be considered a plus:
Experience with Pytest.
Experience with Ansible/Terraform
Experience working with Kubernetes/OpenShift, troubleshooting issues with them, and working with YAML, Kubernetes controllers, and operators.
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