Principal Software Engineer, Storage Infrastructure
Core
Design, build, and evolve distributed storage systems and file systems for cloud-scale AI training and inference workloads, powering the next generation of LLM systems.
Role type
Principal Software Engineer, Storage Infrastructure
Builds
Distributed storage stacks, file systems, and KV caching architectures for large Kubernetes clusters supporting GPU-accelerated AI workloads.
Domain
Cloud Infrastructure, Distributed Systems, AI/ML Infrastructure
Deliverable
production ML models
Required skills
Distributed systems design, Storage system architecture, Kubernetes cluster management, High-performance caching, Geo-distributed storage, RDMA/InfiniBand networking, GPU-accelerated environments, Automation and observability, Root cause analysis
Preferred skills
Collective communication libraries, Model/data/pipeline parallelism, Anomaly detection with ML, Disaster recovery design
Technologies
C, C++, C#, Java, JavaScript, Python, Go, Rust, CUDA, Kubernetes, InfiniBand, RoCE
Responsibilities
Architect and operationalize storage stacks for large Kubernetes clusters, Design storage and KV caching architectures to improve LLM inference latency, Lead architecture reviews and influence long-term storage strategy, Analyze complex cross-layer production issues and implement durable improvements, Partner with ML platform teams to deliver end-to-end capabilities for foundation-model pre-training and inference, Mentor engineers and establish engineering practices for secure and reliable cloud services
Seniority
Principal, hands-on IC with mentorship and strategy
