Good understanding of IT systems and technologies, including SQL, Oracle, Linux, Python, and scripting languages.
Highly motivated and proactive, with the ability to take ownership of applications and projects while serving as a key interface between Process Engineering and Automation teams.
Excellent command of the English language, both written and spoken, is mandatory.
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Kubernetes Service Platform Development of managed Kubernetes services with GPU-native orchestration, intelligent scheduling, distributed workload management, cluster lifecycle management, observability, resource isolation, and support for large-scale AI training and inference workloads
AI Model Training and Inference Platform Development of distributed training, model fine-tuning, model deployment, inference acceleration, serverless inference, model APIs, model evaluation, and production-grade LLM and multimodal model-serving capabilities
AI Agent Platform Development of enterprise AI Agent platforms, including Agent building, workflow orchestration, tool integration, retrieval-augmented generation, memory systems, sandbox execution, multi-Agent collaboration, evaluation, observability, security, and large-scale Agent runtime infrastructure
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