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SHIELD is a device-first fraud intelligence platform that helps digital businesses worldwide eliminate fake accounts and stop all fraudulent activity.
Powered by SHIELD AI, we identify the root of fraud with the global standard for device identification (SHIELD Device ID) and actionable fraud intelligence, empowering businesses to stay ahead of new and unknown fraud threats.
We are trusted by global unicorns like inDrive, Alibaba, Swiggy, Meesho, TrueMoney, and more. With offices in LA, London, Jakarta, Bengaluru, Beijing, and Singapore, we are rapidly achieving our mission - eliminating unfairness to enable trust for the world.
Responsibilities
As a DevOps Engineer, you will be responsible for enhancing our current services and application architectures critical to support our cyber fraud and identity solutions. This role requires an extensive knowledge of security concepts and cloud technologies to develop high-performing, high-availability, scalable and efficient application patterns for the cloud. The ideal candidate should be a keen problem solver and a hands-on team player who is passionate about helping businesses stop fraud and abuse.
Job ID: 111568527
Skills:
Java, Rust, Prometheus, OpenStack, Grafana, UNIX, configuration management, Gcp, Linux, Docker, Splunk, automation, Azure, Kubernetes, Python, AWS, micro-services, AliCloud
Skills:
S3, Powershell, Route53, Prometheus, Windows, Lambda, Ec2, Terraform, Gitlab, Aws Cloud, Python, Newrelic, RDS, Bash, Devops, Jenkins, Linux, Kubernetes, SRE, Go, Opensearch, Monitoring, FSX, EKS
Skills:
Dynamics 365, Power Bi, CSS, Power Automate, Svn, Sql, HTML, Jenkins, Git, Javascript, Power Fx, Sharepoint, Teams, Power Apps Canvas
Skills:
PowerShell, Mariadb, Visual Studio, Artifactory, Jira, Grafana, Groovy, Jenkins, Git, Msbuild, Confluence, Influxdb, Gitlab, Python, Conda, NuGet, Conan, Miro
Skills:
Github, Qt, Cmake, PowerShell, Automated Testing, Git, Docker, Linux, Gitlab, Release Engineering, Helm, Kubernetes, Python, Windows build environments, secure SDLC automation, generative AI, Root Cause Analysis, Rancher