Red Hat is seeking a proficient Cloud & AI Platforms Engineer with a strong background in OpenShift and Kubernetes cluster deployment and configuration to join our Cloud & AI Platforms team in Spain or Ireland.
The Red Hat Cloud & AI Platforms Services organization is responsible for the strategy, design, and implementation of the end-to-end customer experience with Red Hat Cloud Services and AI Platforms. Our team delivers world-class support to customers and partners worldwide for our Platform as a Service (PaaS) and Software as a Service (SaaS) offerings. As a global team, we cultivate a transparent and inclusive environment that welcomes different perspectives. We embrace a blameless culture, learning from our failures to drive continuous improvement. This role offers an exciting opportunity to join one of the fastest-growing enterprise software and services companies and a leader in open-source software.
In this role, you will serve as the first line for mitigating customer issues and, at times, lead processes to manage customer incidents effectively. This often involves coordination across diverse teams to ensure a fast and efficient resolution, restoring customer operations swiftly. Your primary focus will be troubleshooting issues related to both Red Hat OpenShift managed clusters and the Red Hat OpenShift AI stack. You will provide clear communications on the status of ongoing incidents and prepare detailed post-incident analyses, including causes, team involvement, and mitigation steps. You will also offer recommendations to prevent similar incidents in the future, which you may share with senior leadership, partners, and customers.
The candidate needs to be allocated in Spain or Ireland, with a preference for a location closer to our major offices (Barcelona, Madrid, Cork, Waterford).
What will you doCommitment to providing exceptional customer experience by using professional communication and applying product knowledge and deep troubleshooting to perform direct actions in cluster environments to resolve various issues.Contribute to global initiatives and projects to constantly reduce customer effort, improve tooling, and design and write automation software to improve efficiency.Act as the direct contact, adviser, and mentor for customer inquiries and issues with their Cloud & AI Platforms Services through our Customer Portal, conference call, and remote access.Proactively analyze cluster status and identify single points of failure and other high-risk architecture issues; propose and implement more resilient resolutions.Record customer interactions, including investigation, troubleshooting, and resolution of issues, to document diagnostic steps and issue resolution and create reusable solutions for future incidents.Responsible for partnering with internal teams and external parties to deliver seamless infrastructure support for Red Hat's Cloud Services & AI Platforms.Strong work ethic, able to work as part of a team and focus on customers and resolving their issues.Be available to perform weekend shift duties on a rotational schedule.What will you bringProven experience in Infrastructure Implementation, Deployment, Administration, and Production Support of container technologies and orchestration platforms (cri-o, Kubernetes, xKS, Docker, OpenShift Container Platform).Exceptional technical, analytical, and troubleshooting skills using tools like curl, strace, oc (kubectl), and Wireshark analysis to investigate and form precise action plans for issue remediation with components such as networking, system performance issues, Kubernetes, OpenShift Container Platform, Service Mesh, and RESTful API calls.Experience working in a Technical Support role that interfaces with Site Reliability Engineers (SRE), Development Engineering teams, and partner vendors to resolve customer issues.Strong DevOps and/or MLOps background, agile concepts, application development, and deployment tools.Experience with application development, ideally with Python or other languages like Go, Java, and C/C++.Knowledge of training, tuning, and serving ML models using tools like Pytorch, Tensorflow, Ray, Kubeflow Pipelines, Jupyter, or similar.Demonstrates solid customer-centric focus, balancing technical expertise and customer interaction while effectively managing competing priorities, learning and teaching modern technologies, and excelling in technical communication and collaboration.The following is considered a plus:
Experience developing and deploying large-scale AI applications and generative AI applications.Experience in training, tuning, and serving ML models using tools like Pytorch, Tensorflow, Ray, Kserve, ModelMesh, Kubeflow Pipelines, or similar.Knowledge of machine learning algorithms and concepts (e.g., supervised learning, unsupervised learning, deep learning) as applied to generative AI.Experience supporting, tuning, and troubleshooting Jupyter environments on Kubernetes systems in production.Experience as a Customer-Facing Site Reliability Engineer (SRE) or SRE or knowledge of SRE procedures, including incident management, monitoring and alerting, capacity planning, and automation of operational tasks.
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