Senior Solutions Engineer, AI Infrastructure

🕒 June 1

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

💻 Solutions Engineer

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VAST Data

WebsiteLinkedInAll Job Openings

501 - 1000 employees

🤖 Artificial Intelligence

💰 $83M Series D on 2021-05

Artificial Intelligence

VAST Data is the data platform company for the AI era, focused on delivering scalable performance and simple data management to enhance productivity for workload-intensive applications. Founded in 2019, it has become the fastest-selling data infrastructure startup in history, specializing in cloud storage, data storage, flash storage, and universal storage. VAST particularly targets innovations in deep learning, all flash, QLC flash, and NVMe technologies, making it a vital player in the data center architecture and storage solutions market.

📋 Description

• Lead technical discovery with customers across infrastructure, platform, ML, data, and executive stakeholders. • Design architectures for large-scale AI, HPC, analytics, and enterprise data workloads. • Help customers evaluate infrastructure involving GPUs, storage, networking, orchestration, and data movement. • Design and execute proofs of concept that validate performance, scale, reliability, and business value. • Translate complex technical requirements into clear solution designs, reference architectures, and deployment guidance. • Debug customer issues across Linux, storage, networking, Kubernetes, schedulers, GPUs, and application workloads. • Build technical assets, demos, runbooks, and field guidance for repeatable customer engagements. • Partner with sales on technical strategy, competitive positioning, and deal execution. • Partner with product and engineering to communicate customer requirements, gaps, and roadmap opportunities. • Help customers move from architecture design to production deployment.

🎯 Requirements

• 8 to 12+ years of technical experience, with significant hands-on infrastructure experience. • Experience building, operating, or architecting production platform infrastructure. • Strong understanding of Linux kernel implementation details, distributed systems including PAXOS and raft, storage implementations details like NAND or write amplification, networking store/forward, load balancing designs, and production operations. • Experience with one or more of: GPU infrastructure, large scale HPC systems, Kubernetes platforms from scratch, MLOps, storage systems, cloud infrastructure, data platforms, or large-scale enterprise infrastructure. • Ability to communicate credibly with engineers, architects, technical executives, and business stakeholders. • Strong discovery, problem-solving, and systems debugging skills. • Comfort operating in ambiguous, fast-moving environments. • Interest in customer-facing technical work, solution design, and business outcomes. • Experience with large-scale GPU clusters, distributed training, inference infrastructure, or AI platforms. • Experience with petabyte-scale storage or high-performance data systems. • Experience with Kubernetes, Slurm, Ray, Spark, or other orchestration / scheduling systems. • Domain Expertise with one or more of these - Lustre, Ceph, Weka, BeeGFS, GPFS, VAST, object storage, or distributed filesystems. • Experience with InfiniBand, RoCE, RDMA, high-performance Ethernet, or NVIDIA/Mellanox networking. • Direct Experience with CUDA, NCCL, DCGM, GPUDirect, checkpointing, dataset staging, or model-serving infrastructure. • Experience across multiple industries or customer environments.