Sr. Technical Alliance Engineer – AI Platform

WEKA•Campbell, CA

2d•$185,000 - $215,000

About The Position

WEKA is seeking a Technical Alliance Engineer with expertise in parallel file systems, storage technologies, AI technologies, and performance benchmarking. The role bridges engineering, product management, and marketing by demonstrating the value of technology integrations through technical content, benchmarking, and certification testing. The engineer will craft technical narratives, develop performance analyses, and engage with customers and partners to explain the advantages of WEKA’s storage solutions. The position is based in Campbell, California. The role involves partnering with alliance organizations to identify product integrations that solve customer problems, validating partner products, and creating use-case-focused benchmarks. It also includes hands-on work with NVMe storage, AI/ML workloads, high-performance file systems, and NVIDIA technologies, as well as creating technical materials, advising engineering teams, delivering presentations and workshops, supporting field and presales teams, and analyzing market trends. WEKA describes itself as a pre-IPO, growth-stage company focused on AI data infrastructure. It emphasizes accountability, bravery, collaboration, and customer centricity, and encourages interested applicants to apply even if they do not meet every listed qualification. The company states that it is an equal opportunity employer.

Requirements

Strong understanding of parallel file systems, such as Lustre, IBM Spectrum Scale, WekaFS, or BeeGFS.
Expertise with storage benchmarking tools, such as FIO, IOzone, mdtest, IOR, Elbencho, or SPECStorage.
Hands-on experience with infrastructure setup and configuration.
Strong knowledge of NVMe storage and its role in high-performance computing and AI/ML workloads.
Solid understanding of AI/ML workflows and how they interact with storage architectures.
Experience with NVIDIA GPU architectures, GPUDirect Storage (GDS), and Spectrum-X networking.
Deep knowledge of file system internals, storage networking, and data management technologies.
Experience in a storage lab environment, including setting up test environments and troubleshooting performance issues.
Ability to create technical content and presentations for technical and business audiences.
Excellent communication skills and ability to explain complex technical concepts clearly.
Strong knowledge of virtualization and containerization technologies.

Nice To Haves

Hands-on experience with Kubernetes.
Experience with containerized and cloud storage architectures.
Familiarity with RDMA, InfiniBand, RoCE, and high-speed networking.
Prior experience as a TME, Solutions Architect, or Storage Performance Engineer at a storage-focused company.

Responsibilities

Work with alliance partners to identify product integration opportunities that jointly solve customer problems.
Conduct partner certification and validation.
Develop and execute benchmarking methodologies to measure and showcase parallel file system performance, emphasizing use-case-based benchmarks and product differentiation.
Work hands-on with NVMe storage, AI/ML workloads, and high-performance file systems to optimize performance and validate use cases.
Apply experience with NVIDIA technologies, including GPUDirect Storage (GDS), GPU architectures, Spectrum-X networking, and accelerator architectures, to enhance storage performance and AI/ML workloads.
Create technical content, including whitepapers, blogs, presentations, and solution briefs.
Collaborate with engineering teams and provide feedback on product features and performance tuning.
Deliver technical presentations, webinars, and hands-on workshops to customers and partners.
Evaluate partner product features and replicate customer scenarios.
Support field teams with technical insights and assistance in presales engagements.
Analyze market trends in storage, NVMe, AI/ML workloads, and GPU-accelerated computing to refine messaging and competitive positioning.