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VAST Data

The Data Platform company for the AI era.

Senior Solutions Engineer, AI Infrastructure

Solutions EngineerSolutions EngineerFull TimeRemoteSeniorTeam 501-1,000H1B SponsorCompany SiteLinkedIn

Location

United States

Posted

1 day ago

Salary

0

Seniority

Senior

Job Description

Senior Solutions Engineer, AI Infrastructure

VAST Data

• 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.

Job 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.

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