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Hewlett Packard Enterprise

Builds servers, networking and private cloud

Storage Architect – Presales

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • At least 7 years of experience designing, implementing, or supporting enterprise storage and data architectures.
  • A bachelor's degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience.
  • Strong customer-facing architecture, consulting, or presales experience.
  • Strong foundational knowledge of S3 object storage, including buckets, objects, APIs, authentication, data protection, and common application integration patterns.
  • Working knowledge of enterprise file protocols, particularly NFS and SMB.
  • Experience sizing storage solutions based on capacity, performance, growth, network, and application requirements.
  • Ability to plan, configure, execute, and troubleshoot technical proofs of concept.
  • Understanding of modern AI and analytics data pipelines, including AI inference, Retrieval-Augmented Generation, vector databases, data lakes/Lakehouses, and large-scale analytics workloads.
  • Ability to discuss storage in the context of data flow, data lifecycle, data management, protection, governance, and application consumption.
  • Strong understanding of storage performance concepts, including throughput, latency, IOPS, metadata performance, concurrency, and network bandwidth.
  • Willingness and ability to travel for customer engagements.

Responsibilities

  • Partner with customers to architect scalable file and S3 object storage solutions for AI, analytics, and enterprise workloads.
  • Understand application data flows, data lifecycle requirements, and performance characteristics to recommend appropriate storage architectures.
  • Size storage solutions based on capacity, throughput, latency, network bandwidth, growth, availability, and workload requirements.
  • Lead technical workshops, assessments, benchmarks, and hands-on proofs of concept.
  • Apply knowledge of AI inference, Retrieval-Augmented Generation, data lakes, and analytics pipelines to storage architecture and design decisions.
  • Collaborate with product management and engineering to translate customer requirements into product and roadmap priorities.
  • Bring competitive knowledge and market awareness to customer discussions and internal strategy.
  • Architect and document enterprise-scale file and object storage solutions.
  • Analyze customer data flows, workloads, growth patterns, and data management requirements.
  • Size storage environments for performance, capacity, resiliency, and scalability.
  • Lead and execute hands-on proofs of concept validating performance, integration, scalability, and operational requirements.
  • Design storage architectures for AI inference, Retrieval-Augmented Generation, analytics, and data lake workloads, considering throughput, latency, metadata, network design, and data accessibility.
  • Help customers understand how data is ingested, stored, processed, protected, moved, governed, and consumed across modern data pipelines.
  • Translate customer requirements and field experience into actionable product feedback and roadmap recommendations.
  • Provide competitive analysis, technical positioning, and solution guidance to sales and technical teams.
  • Present architectures and technical recommendations to executive and deeply technical audiences.
  • Support strategic presales engagements, requests for information/proposals, solution sizing, and technical justification.
  • Travel as needed to support customers, partners, and strategic opportunities.

Desired Qualifications

  • Experience with AI inference and Retrieval-Augmented Generation architectures, vector databases, embeddings, and retrieval workflows; data lake and Lakehouse architectures; analytics platforms and distributed query engines; GPU-based infrastructure and AI data pipelines; high-throughput data ingestion and processing; S3-based application architectures; data movement between compute, storage, cloud, and AI platforms; and performance characterization and workload benchmarking.
  • Experience with enterprise file or object storage platforms such as Dell PowerScale/ObjectScale, Pure Storage FlashBlade, NetApp ONTAP/StorageGRID, VAST Data, Scality, or other enterprise file or S3-compatible object storage platforms.
  • Familiarity with AWS, Azure, and Google Cloud Platform storage services and integration patterns.
  • Understanding of hybrid and multi-cloud data architectures.
  • Knowledge of modern AI and analytics platforms and their storage requirements.
  • Awareness of the competitive enterprise file and object storage landscape.
  • Experience in technical presales, consulting, solution architecture, or customer advisory roles.

About the Company

Hewlett Packard Enterprise

Builds servers, networking and private cloud

Hewlett Packard Enterprise sells servers, storage, networking and hybrid cloud software to large companies, governments and service providers. Its GreenLake platform lets customers run on-premises hardware as a metered cloud service, and its Cray supercomputers run national lab and AI training workloads. The networking business, built on Aruba and Juniper Networks, supplies campus, data-center and routing equipment. Revenue comes from hardware sales, multiyear support contracts, financing and subscriptions. The company traces its roots to Hewlett-Packard, founded in 1939, became a separate public company in 2015 and is headquartered in Houston, Texas.

Company size
10,001+
Company stage
IPO
Headquarters
Houston, TX
Founded
1939

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