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Minimum of 3 years; experience with one or more of the following: Splunk Phantom, Microsoft Sentinel, Cortex XSOAR, Google Chronicle (previously Siemplify), or other automation tools Minimum of 3 years’ experience with developing scripts and integration in other development scripting and languages (e.g., Python, PowerShell, Java, JavaScript.
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AWS Certified Solutions Architect - Associate or equivalent (e.g., Azure Administrator Associate, Google Cloud Associate Cloud Engineer) requiredSystems & Technology. They work closely with development and operations teams to enhance cloud-based applications and implement automation for efficiency.
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Familiar with automated development lifecycles and pipelines (DevOps, DevSecOps)Project management experience with Agile (Kanban/Scrum)Experience with cloud security strategy, cloud provider ecosystems (Amazon AWS/Microsoft Azure)Knowledge of cloud networking architecture, cloud operations, security, automation, and orchestration.
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Experience with cloud platforms (AWS, Google Cloud Platform, Openstack), CI/CD, and Agile methodologies. The Senior Quality Assurance Test Automation Analyst within Enterprise Systems Department (ESD) primary responsibility will be to build a test automation infrastructure and Framework that leverages DevSecOps, Continuous Integration/Continuous Delivery aspects and performing a variety of activities relating to various projects and production support for Georgia Tech Research Institute (GTRI.
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Configuring and managing cloud rendering solutions like Deadline on AWS or Google Cloud. Automation with systems like Ansible, JAMF, and Jenkins. You’ll be involved in projects supporting concept design, prototyping, delivery to engineering, review, asset management, workflow automation, and distributed rendering/ compute.
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World WideTechnology, Inc. has an opportunity available for an Infrastructure Engineer focused on supporting cloud technologiesinMicrosoft Azure, Google Cloud Platform and Oracle Cloud.
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We are looking for a senior QA test automation engineer who would be responsible for testing and validating scalable microservices built using a combination of Java and Google cloud platform technology stack.
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Position SummaryAs a Lead ML/AI Engineer, you will drive the design and implementation of functionality related to the end-to-end ML/AI and Feature lifecycle management on Azure/Google Cloud Platform, leveraging and integrating the cloud native services with other standard operational and automation tools.
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We engineer business outcomes for Fortune 500 companies and digital natives in the technology, healthcare, insurance, travel, telecom, and retail & CPG industries using technologies such as cloud, microservices, automation, IoT, and artificial intelligence.
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About the job As a Generative AI Field Solutions Developer, you will support Google Cloud sales organization. You will be responsible to construct rapid prototype Generative AI applications tailored to Google Cloud customers, catering to a diverse clients ranging from early stage startups to prominent companies.
$215,000 - $315,000 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Hands on experience in DevOps related tools Harness, Gitlab, Github, Gitlab runner , Maven , Docker , Kubernetes, Google cloud , linux server. Hands-on experience in various automation tools such as Jenkins and Gitlab as continuous integration, GitLab/GitHub/Bitbucket as SCM , Harness as continuous deployment, Ansible, chef and puppet, Cobertura, Maven Plugins , Sonar, Jasmine, ServiceNow and Confluence.
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2+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud) Utilize programming languages like DataBricks, SQL, Python, and RDBMS and NoSQL databases and Cloud based data warehousing services such and Snowflake.
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Experience with CI/CD Tools (Jenkins, GitHub) for Apigee proxies deployment automation. Experience hands on working knowledge on Linux based infrastructure and google Kubernetes engine.
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Conduct in-depth security assessments and audits of cloud environments, utilizing tools such as AWS Inspector, Azure Security Center, or Google Cloud Security Command Center. Expert-level proficiency in AWS, Azure, or Google Cloud Platform, substantiated by current associate, specialty, or professional cloud platform c ertifications.
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Experience with public cloud service providers (e.g. Amazon AWS, Google GCP, Microsoft Azure). Design, architect, and implement defensive security controls across Palantir’s multi-cloud multi-tenant SaaS infrastructure based on Kubernetes, OpenShift and several other popular open-source technologies.
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