Senior Systems Software Engineer - Data Path

LT ZERO Asia Pacific•Centennial, CO

2h•$160,000 - $200,000•Hybrid

About The Position

Quantum is seeking a high-caliber Senior Systems Software Engineer to join our Core Storage Team. In this role, you will be responsible for the "brain" of our distributed storage system: the Data Path. You will design, implement, and optimize the software layers that handle I/O requests from the moment they hit the network interface until they safely persisted across a cluster of nodes. This is a deep-systems role requiring a passion for low-latency code, concurrency, and distributed systems theory.

Requirements

Minimum 15 years of experience using C/C++ or other equivalent skills for development.
Ability to work in a team environment.
Strong communication skills.
Ability to work with a remote team.
Self-motivated, able to identify and solve problems on their own.
Ability to collaborate cross functionally and integrate other components into the solution.
Approach problems creatively and not just repeat the same mistakes made before them.
Effective communicator to both technical and non-technical audiences.
Willing and able to come into our Centennial, CO or Mendota Heights, MN office during core business hours (10am - 4pm local) Tuesday - Thursday.

Nice To Haves

Experience with containers and Kubernetes is a plus.
Experience with Linux I/O subsystem, networking is a plus.
Experience with Storage protocol, clustering design and development is a plus.
Experience with any AI tools or programming is a plus.
Experience with NAS protocols like SMB and NFS is a plus.
Experience in Linux operating system, able to perform installs, upgrades, maintenance and configuration.
Experience using GIT.
Experience using JIRA.

Responsibilities

Design and maintain scalable, high-performance data path components including distributed caching, metadata management, and data placement algorithms.
Identify and eliminate bottlenecks in the I/O path. You will work with technologies like NVMe-over-Fabrics (NVMe-oF), RDMA, and zero-copy data transfer techniques to achieve microsecond-level latency.
Implement complex features like erasure coding, snapshots, thin provisioning, and background data scrubbing to ensure 99.9999% data durability.
Manage high-concurrency challenges, utilizing lock-free data structures and asynchronous programming models to maximize multi-core CPU utilization.
Ensure the data path scales linearly as nodes are added to the cluster, managing rebalancing and reconstruction without impacting client performance.