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.
We are seeking a Backend Software Engineer to join the Control Plane team for the DDN Infinia AI Data Platform. This role is critical in building the core backend services that power manageability, API-driven control, automation, and intelligent supportability across large-scale hybrid (OnPrem + cloud) environments. You will design and develop highly scalable, secure, and resilient backend systems that enable centralized orchestration, lifecycle management, policy enforcement, and integration with external systems. This role also involves enhancing API frameworks, improving supportability, and embedding security best practices across the platform. This is a hands-on technical leadership role focused on building foundational services that operate reliably at petabyte scale and support mission-critical AI/data workloads. KEY RESPONSIBILITIES - Design and build scalable, high-performance distributed backend services powering the platform control plane. - Develop APIs for centralized management of storage and compute across multi-region hybrid (OnPrem + cloud) environments. - Architect and implement resilient microservices with strong consistency, fault tolerance, high availability, and low latency at petabyte scale. - Contribute to the evolution of an API-first platform, designing clean, versioned, extensible APIs (REST/gRPC) for control, automation, and integration. - Own API lifecycle management including versioning, backward compatibility, deprecation strategies, and governance; ensure APIs are intuitive, consistent, and well-documented. - Enable APIs to support automation, policy-driven workflows, and ecosystem integrations. - Build backend systems supporting provisioning, scaling, upgrades, configuration, and full lifecycle management. - Implement policy-driven orchestration and Infrastructure-as-Code (IaC) integrations. - Support RBAC, multi-tenancy, and enterprise-grade self-service capabilities. - Instrument services with logs, metrics, traces, and events to enable deep observability, automated diagnostics, troubleshooting, and incident resolution. - Contribute to alerting, incident correlation, and root cause analysis capabilities to improve operational transparency and supportability. - Design and implement secure-by-design systems with strong authentication, authorization, RBAC, encryption (in transit and at rest), and audit logging. - Collaborate with security teams to ensure compliance with enterprise and regulatory standards. - Design systems for fault tolerance, graceful degradation, disaster recovery, and seamless upgrades/rollbacks with minimal or zero downtime. - Drive engineering excellence through code reviews, design reviews, and adherence to best practices. PROGRAMMING & TECHNOLOGY REQUIREMENTS - 5+ years of experience in backend or distributed systems engineering - Strong experience designing and building microservices-based architectures - Proficiency in at least one modern backend language (e.g., Go, C++, Java, Python, or similar) - Experience designing and implementing APIs (REST and/or gRPC) - Deep understanding of distributed systems concepts (consistency, availability, partition tolerance, etc.) - Experience with cloud-native architectures and containerized environments - Strong knowledge of security principles including authentication, authorization, and encryption - Strong understanding of object-oriented design, data structures, and algorithms. - Experience building and maintaining large-scale distributed systems using modern software engineering practices. - Experience with containerized environments and orchestration (e.g., Kubernetes). - Knowledge of CI/CD pipelines and automated testing frameworks. SUCCESS METRICS - Delivery of robust, scalable backend services supporting control plane operations - High-quality, well-documented, and stable APIs with strong adoption - Reduced operational friction through automation and improved supportability - Strong system reliability, performance, and uptime at scale - Secure, compliant services with minimal vulnerabilities and audit issues - Successful deployment and operation across both OnPrem and cloud environments - Positive collaboration and influence across engineering teams