Cloud Engineer
R SystemsDenver, CO, US1 day ago
Job type
- Full-time
Job descriptionKnowledge of enterprise cloud solutions, deploying and running solutions in a cloud environment, and private, public, and hybrid clouds Extensive experience with Internet technologies and protocols like TCP / IP, VPN, SSL and HTTP Hands-on experience with public and private cloud services (Azure, AWS, Openstack, VMWare, ect) as well as load balancers and networking devices Experience designing high availability and disaster recovery / fail-over infrastructures Development experience with database or application integration technology Deep knowledge of Linux fundamentals Knowledge of open-source architectures and / or past contributions to open-source projects Design, development and operations experience with highly available, scalable, and fault tolerant systems Experience with Data Science project lifecycle (Azure ML Studio, AI Foundry, Key Vault, Fabric, Storage Account, Language Studio, EventHub, Azure Functions, App Service, Logic Apps, API Management, Microsoft Purview, Azure Cosmos DB, Azure Kubernetes Services (AKS), Azure Container Apps, Azure Container Instances (ACI), Managed Endpoints, Private Endpoint, Virtual Network) Experience with agile / scrum methodologies Professional Cloud Solutions Architect (PCSA) Certification. 2+ years of experience.
Produce architecture blueprints that guide the development and implementation of Cloud solutions across multiple products, providing direction to technical teams during project delivery and ensuring implementations support technology and product roadmaps. The Cloud Solutions Architect provides their expertise in the development and maintenance of architecture standards and solutions that align with strategic goals and partner with product managers, business analysts, designers, and software engineers to navigate solution decisions.
Responsibilities :
- Design, implement, and manage scalable cloud infrastructures in Azure to support AI model deployments, ensuring high availability and reliability.
- Collaborate with the AI Engineering team to streamline the deployment of machine learning models, optimizing the use of cloud resources for performance and cost-efficiency.
- Develop and enforce security best practices for Azure resources, including identity and access management, data protection, and compliance monitoring.
- Troubleshoot and resolve issues related to cloud infrastructure and model deployments, ensuring minimal downtime and efficient problem resolution.
Skills and Knowledge :
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Cloud Engineer • Denver, CO, US
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