Plan, Develop & Customize MES : Plan, support, customize, and further develop the Manufacturing Execution System (MES), including managing installations on container infrastructure and ensuring alignment with the template team, BMI team and supplier (Critical Manufacturing).
Requirement Engineering & Supplier Coordination: Define, document and track requirements with the supplier, translate user needs into features/user stories/tasks in DevOps, and ensure adherence to source‑code management processes.
Process Design, Configuration & Master Data Management : Streamline, configure, and customize MES processes, including creating suitable master data and preparing new process concepts for user-level presentation and explanation.
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This role is for an experienced software developer who will build front-end experiences using modern frameworks, notably React. In this role, you will work with other software engineers, designers, and product owners to build internal systems. You will develop and test software systems for enhancements and new products including cloud based solutions. You will need to analyze requirements, write tests, and integrate application components. Be well versed in the latest development methodologies like Scrum, DevOps, and test driven development. Should also enable solutions that take into account APIs, security, scalability, manageability, usability, and other critical factors that contribute to complete solutions. We welcome your innovative ideas and fresh perspectives to strengthen our growth mindset culture that is grounded in customer obsession, diversity and inclusion.
Transforming Hyperscale Power into Useful AI: We take the extreme complexity of gigawatt-scale energy grids, liquid-cooled data center topologies, and low-latency networking fabrics, and turn that raw physical power into accessible, high-performance AI Cloud that directly drives real-world intelligence.
Building an Integrated Full-Stack Cloud Platform: We engineer the complete software layer, spanning bare-metal provisioning, managed Kubernetes, distributed training pipelines, high-throughput AI Inference engines, and Model-as-a-Service (MaaS) with serverless APIs, empowering enterprises to seamlessly train, fine-tune, deploy, and serve next-generation AI intelligence.
Cloud Service Platform Development of large-scale, highly available AI cloud services, including GPU virtual machines, bare-metal services, container services, cloud networking, storage, billing, monitoring, security, and multi-region resource management
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