Staff Software Engineer, AI Data Platform

About the role

DDN is seeking a Staff Software Engineer to act as Technical Lead for its Data Ocean initiative within the DDN AI Data Platform. The role defines the technical vision, architecture and execution strategy for next-generation data management capabilities such as intelligent caching, global namespaces, data tiering and data mobility across hybrid storage environments. It is a hands-on technical leadership position for an experienced distributed systems engineer who also mentors engineering teams.

Key responsibilities

• Own the technical vision, architecture and roadmap of the Data Ocean platform and lead implementation of core capabilities
• Design, develop, debug and optimize production-quality C/C++ code for performance-critical distributed storage services
• Build scalable solutions for data movement, metadata management, caching, global namespace services and data mobility
• Architect high-performance data path and control plane services integrating object, file and block storage across on-premises and hybrid cloud environments
• Solve distributed systems challenges around consistency, replication, fault tolerance, concurrency and large-scale coordination
• Lead architecture reviews, design discussions and code reviews, and mentor engineers
• Partner with Product Management, Engineering and Architecture to turn product requirements into production-ready software
• Drive performance analysis, profiling, optimization, automated testing and CI/CD practices

Required profile

• Bachelor's, Master's or Ph.D. in Computer Science, Electrical Engineering or a related field
• 10+ years of experience developing enterprise storage systems or distributed systems software
• Proven experience as a Principal Engineer, Senior Staff Engineer or Technical Lead
• Experience leading architecture and technical execution across cross-functional, globally distributed teams

Required skills

• Expert-level C/C++ programming
• Distributed systems: consistency models, replication, fault tolerance, coordination, concurrency and scalability
• Object storage, distributed file systems, block storage and cloud storage architectures
• Production-scale distributed storage platforms