Drimva

Pure Storage

Senior Pre-Sales Systems Engineer, Higher Education (Texas)

$141K–$212K

Remote, Texas +1 · Remote · Senior · Full-time · Posted Oct 29, 2026

Location
Remote, Texas
Texas, United States
Experience
8 or more years of relevant experience across technology, solution design, and customer-facing communication.
Education
BS in CS, EE, another technical degree, or equivalent experience.

About the job

Leads pre-sales technical engagements for Texas higher-education accounts, designing and positioning solutions that support research, HPC, AI, data management, and institutional goals.

What you'll do

  • Build technical and financial cases, tailor discussions to institutional stakeholders, and connect solutions to research and operational outcomes.
  • Lead evaluations, benchmarks, proofs of concept, configurations, and technical responses to RFIs, RFPs, and RFQs.
  • Support research data and workloads across HPC and AI pipelines, retention, governance, compliance, and archiving.

What they ask for

  • 8 or more years of relevant experience across technology, solution design, and customer-facing communication.
  • Pre-sales or customer-facing technical experience, plus experience with higher education, research computing, academic medical centers, or the public sector.
  • Familiarity with HPC and AI environments, including parallel and distributed file systems, GPU-attached storage, schedulers such as Slurm, and research data pipelines.
  • Broad technical depth across two or more listed domains; value-based selling track record; BS in CS, EE, another technical degree, or equivalent experience.

Nice to have

  • Knowledge of storage architectures and file systems; Linux, NFS, networking, virtualization, cloud, containers, databases, or analytics platforms.
  • Experience with grant-funded procurement, consortium purchasing, or public sector contract vehicles.

Pay

$141,400 — $212,100 USD annual base salary

Tools

HPC, AI, Slurm, FC, iSCSI, NAS, SAN, Kubernetes

AI focus

Supports customer research and institutional AI environments, including GPU-attached storage and data pipelines for research workloads.

Model-written summary · the original posting is authoritative

First seen Oct 30, 2026 · Last verified Nov 5, 2026 (UTC)