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Amazon Web Services (AWS) or Google Cloud Platform (GCP) administration experience. Hands on experience in deployment and management of routing, switching, wireless, and security appliance technologies using vendors such as Cisco, Palo Alto Networks, and Meraki.
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Cloud Infrastructure Deployment: Lead the deployment and management of AI services on cloud platforms such as AWS, Google Cloud, and Azure for scalability, security, and cost optimization.
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You will also be responsible in building healthy DevOps platform with policies and procedures around implementing and supporting our global hybrid cloud container strategies using Kubernetes deployed in Google Cloud Platform (GCP) and Amazon Web Services (AWS.
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Experience with AWS, Microsoft Azure or Google Cloud Platform configuration and administration of security features and services (including identity and access management, networking, firewalls, encryption.
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Experience working with cloud infrastructure, AWS, Azure, and/or Google Cloud Platform in particular. Database Query Engine (QA), Automation Infrastructure and Quality Engineering (AIQ), Cloud Platform & Deployment Engineering, Developer Productivity Engineering (DPE.
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Snowflake started with a clear vision: develop a cloud data platform that is effective, affordable, and accessible to all data users. Snowflake developed an innovative new product with a built-for-the-cloud architecture that combines the power of data warehousing, the flexibility of big data platforms, and the elasticity of the cloud at a fraction of the cost of traditional solutions.
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Cloud Platforms: Familiarity with cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) for deploying and managing applications in the cloud.
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Strong experience with InfoBlox DNS solution, AWS Route 53, Google Cloud DNS and F5 GTM & LTM. Experience with Cloud (AWS & GCP) Network Component in hybrid model with on-prem Network connectivity.
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Multi-cloud release automation. Experience with DevOps (Jenkins, Ansible, Terraform) and Containerization (Kuberneters, Docker) a plus. Experience building automation frameworks and infrastructure to improve efficient of development workflow.
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Minimum of 5 years of experience in a Cloud Engineering or DevOps role with knowledge of AWS, Azure, or Google Cloud platforms. The Senior Platform Engineer will leverage their experience and expertise to develop the strategy, design, and implementation of CI/CD pipelines for cloud-native applications, as well as large-scale projects hosted in either AWS or Azure.
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Excellent Experience with infrastructure as code using tools like Terraform, or Google Cloud Deployment Manager. Advanced understanding of cloud infrastructure, with a strong focus on Google Cloud and experience in Azure or AWS.
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Build and maintain the Atlas Serverless infrastructure across AWS, Azure, and Google Cloud. Has built large scale infrastructure, especially within a context of a SaaS/PaaS system, on at least one of the major public cloud providers like AWS, Azure, and Google Cloud (or comparable equivalence.
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Implement major infrastructure management platforms (e.g., BMC, HP, CA, VMWare), automation, and orchestration (e.g., Ansible, Chef, Puppet) and public cloud vendors (e.g., AWS, Rackspace, Google Cloud Platform, Azure, and Office 365.
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Experience with Cloud platforms like Microsoft Azure, AWS, Google Cloud. Experience with cloud deployment technology (Docker, Ansible, Terraform, etc.) Exposure to Docker, Kubernetes, and cloud services is beneficial.
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Experience with cloud computing platforms and services (e.g., AWS, Azure, Google Cloud) for scalable machine learning infrastructure and deployment. Experience with deployment and optimization of machine learning models on embedded systems and edge devices.
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