Staff Storage Platform Engineer (AI Storage) - Remote
Radian Arc · Engineering · Lead · 1mo ago
Anyone, anywhere in the world can apply.
AI review: Checked the employer's own posting (https://job-boards.eu.greenhouse.io/radianarc/jobs/4875788101). Evidence: "This is a fully remote role, we will consider relevant candidates in all locations."
Applies on the original listing · via Himalayas
Who can apply
Read straight from the listing, so you know before you spend time on it.
Anyone, anywhere in the world can apply.
“This is a fully remote role, we will consider relevant candidates in all locations.”
- Async-first
- The listing doesn't promise async-first working.
- Contractor / B2B
- No mention of hiring international contractors or invoicing.
- Global stipend
- No home office or equipment budget mentioned.
- Annual retreat
- No company-paid get-togethers mentioned.
Read from the listing automatically. Always confirm the details with the company before you accept an offer.
About the role
As the first dedicated storage platform engineer at Radian Arc, you will hold architectural ownership and lead hands-on technical execution across edge and core AI storage infrastructure. You will design, scale, and optimize platforms supporting distributed inference stacks, model training, and fine-tuning workloads across hyperconverged setups, local NVMe, and disaggregated AI storage solutions like Weka and VAST Data.
What you'll do
- Design and implement scalable AI storage architectures supporting both edge and core GPU deployments.
- Define storage strategies for distributed inference, fine-tuning, training workloads, and KV-cache persistence.
- Architect solutions across hyperconverged infrastructure (such as StorPool), local NVMe storage, and disaggregated storage platforms (such as Weka and VAST Data).
- Establish reference architectures, design principles, and automation standards for storage platforms across the organization.
- Debug complex cross-layer performance issues spanning storage hardware, networking, Linux kernel I/O paths, and Kubernetes CSI integrations.
What you bring
- Strong hands-on experience designing and operating distributed storage systems for high-performance compute and GPU-accelerated environments.
- Proven experience designing storage architectures for large-scale AI inference or training platforms, including dataset distribution and checkpointing.
- Deep technical knowledge of the Linux storage and I/O stack, NVMe devices, storage fabrics, and high-performance data paths.
- Experience with enterprise AI/HPC storage platforms such as WEKA and Kubernetes storage integrations (CSI).
- Strong automation skills in Python and/or Bash, alongside demonstrated technical leadership and cross-functional influence.
About Radian Arc
Radian Arc specializes in outcome-optimized AI infrastructure, deploying, orchestrating, and monetizing GPU compute inside telco networks, at the edge, and in core data centers.
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