At a glanceSummarised by Seekless from the posting.
Must have7
15+ years of experience developing large-scale systems software using C/C++
10+ years of hands-on experience designing and developing storage systems, distributed storage platforms, or high-performance I/O subsystems
Deep understanding of storage architecture, I/O optimization, memory management, caching, scheduling, and data path design
Experience with distributed storage concepts, including erasure coding, replication, recovery, and fault tolerance
Hands-on experience with SPDK or similar high-performance user-space storage frameworks
Strong knowledge of concurrency, synchronization, and distributed systems design
Expertise in performance analysis, profiling, debugging, and system optimization
Nice to have5
Experience with high-performance computing (HPC), AI infrastructure, or large-scale storage platforms
Experience with distributed file systems, object storage, or hybrid storage architectures
Knowledge of NVMe-oF, RDMA, and high-speed networking technologies
Experience building observability, monitoring, and self-healing infrastructure
Familiarity with containerized workloads and cluster orchestration
Skills
C
C++
SPDK
NVMe-oF
RDMA
Role Overview
We are seeking a Senior Staff Storage Backend Engineer to design and optimize the next generation of high-performance distributed storage systems. This role focuses on building the core I/O path, improving scalability, reliability, and software quality across large-scale storage clusters.
The ideal candidate has deep expertise in C/C++, distributed systems, storage architecture, and performance optimization, with a proven track record of building highly available, low-latency infrastructure.
Key Responsibilities
Storage Architecture & Development
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Design, develop, and optimize high-performance storage I/O paths for extreme throughput, low latency, and high concurrency.
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Build and improve distributed storage components, including erasure coding, data protection, recovery, and data layout algorithms.
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Develop scalable concurrency models, locking mechanisms, and fault-tolerant designs.
Performance & Scalability
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Analyze and optimize storage performance across CPU, memory, caching, scheduling, and data movement paths.
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Drive profiling, benchmarking, and performance tuning across multi-node, multi-device environments.
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Design asynchronous, event-driven architectures supporting AI workloads, high-speed data pipelines, and real-time analytics.
Technical Leadership
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Serve as a technical leader for the IO Path team, driving architecture decisions, design reviews, code reviews, and complex debugging efforts.
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Partner with engineering leadership to define technical strategy, evaluate new technologies, and influence the product roadmap.
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Mentor engineers and promote engineering excellence through strong engineering practices and rigorous technical reviews.
Quality & Cross-Functional Collaboration
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Collaborate with QE, storage, networking, performance, field, and support teams to deliver reliable enterprise-class software.
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Partner with QE to identify quality gaps, improve validation strategies, and ensure robust coverage of complex distributed storage scenarios.
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Debug complex customer and system issues and translate learnings into product improvements.
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Influence CI/CD pipelines, automation frameworks, and release processes to enable scalable and reliable software delivery.
Required Qualifications
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15+ years of experience developing large-scale systems software using C/C++.
•
10+ years of hands-on experience designing and developing storage systems, distributed storage platforms, or high-performance I/O subsystems.
•
Deep understanding of storage architecture, I/O optimization, memory management, caching, scheduling, and data path design.
•
Experience with distributed storage concepts, including erasure coding, replication, recovery, and fault tolerance.
•
Hands-on experience with SPDK or similar high-performance user-space storage frameworks.
•
Strong knowledge of concurrency, synchronization, and distributed systems design.
•
Expertise in performance analysis, profiling, debugging, and system optimization.
Preferred Qualifications
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Experience with high-performance computing (HPC), AI infrastructure, or large-scale storage platforms.
•
Experience with distributed file systems, object storage, or hybrid storage architectures.
•
Knowledge of NVMe-oF, RDMA, and high-speed networking technologies.
•
Experience building observability, monitoring, and self-healing infrastructure.
•
Familiarity with containerized workloads and cluster orchestration.