DDN provides high-performance data intelligence and storage platforms that enable rapid, low-latency, high-throughput data access for NVIDIA GPU clusters, accelerating AI, LLM, GenAI, RAG, and HPC workloads.
Our DevOps team is at the forefront of innovation, driving high-performance and highly scalable emerging technologies with Infinia Software Defined Storage (SDS). Infinia SDS is designed to support multiple client protocols, delivering robust, enterprise-grade storage solutions for cutting-edge use cases. With a global presence of expert developers, QA, and DevOps engineers, we are transforming the way software-defined storage operates in both on-premises and cloud environments. WHY JOIN US? We provide a unique blend of on-premises and cloud DevOps—more than just managing infrastructure, you will have the chance to deploy critical applications on Kubernetes and shape infrastructure as code (IaC) from the ground up. Here’s a glimpse of the exciting work we do: - Infrastructure-as-Code: Constantly evolving our infrastructure with Terraform, Python, and Bash, building cloud infrastructure on GCP with future plans to expand into other cloud providers. - On-Premises Excellence: Develop and deploy self-sustaining infrastructure that delivers mission-critical applications faster, while enhancing flexibility and performance. - Build and Release Acceleration: Engineer build acceleration solutions by integrating with Nexus/JFrog Artifactory, streamlining build workflows, and connecting tools to self-managed artifact repositories. CUTTING-EDGE TOOLS WE USE: Our infrastructure and tooling reflect our commitment to modern DevOps practices. Here’s how we empower engineers to stay at the top of their game: - Kubernetes and ArgoCD: Orchestrate scalable deployments with Kubernetes and leverage ArgoCD for automated and declarative application management. - Packer + MaaS: Create custom bare-metal images with Packer and deploy them seamlessly using MaaS (Metal as a Service) for Ubuntu. - K3s + KubeVirt: Build a self-provisioning VM environment to empower developers and QA engineers. - Infinia & Harbor: Utilize Infinia for S3 storage services, and Harbor for container image management. - GitHub Enterprise (GHE) + Actions: Collaborate using GHE, with DevOps leading the development and maintenance of workflow actions for CI/CD pipelines. - Docker: Build containerized environments for both cloud and on-prem applications. - Quay & GCS Buckets: Manage external artifacts with Quay and Google Cloud Storage (GCS). WHAT YOU’LL WORK ON: - Self-Deployable Environments: Our DevOps engineers are building a seamless, self-service environment to empower developers and QA teams. - Bare-Metal & Cloud Integration: Get hands-on experience with bare-metal provisioning using MaaS, while deploying infrastructure in hybrid models with GCP and expanding to other cloud providers. - Streamlining Build Systems: We integrate tools like Nexus/JFrog Artifactory to accelerate builds and optimize workflows, ensuring smoother development and faster delivery. - Constant Innovation: We believe in continuous improvement, constantly enhancing infrastructure-as-code to make deployments faster, more reliable, and easily replicable. REQUIRED SKILLS: All of the following skills are mandatory: - Application Deployments within Kubernetes using tools like Helm or ArgoCD. - Cloud experience with Oracle Cloud Infrastructure (OCI) is a plus; experience with other cloud providers is good to have. - Docker experience. - Configuration Management with Ansible or similar tools. - Monitoring and Metrics using Prometheus, Grafana, or equivalent. - Bash Scripting expertise. - CICD Pipeline Development using GitHub/GitLab, Jenkins, and related tools (e.g., YAML, Groovy). - Basic Linux Proficiency for underlying infrastructure management. PREFERRED SKILLS: The following skills are desirable but not mandatory: - Linux Administration, Networking, and Troubleshooting. - On-prem Kubernetes Deployment and Administration. - Virtualization experience. - Python or Golang programming knowledge. - CI/CD pipeline automation and scripting using languages like Python or Groovy. - CI system integration and optimization experience.