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# Presales Storage Architect, Unstructured Data - Expert(e) Avant Vente Architecte H/F

- **Company:** Hewlett Packard Enterprise
- **Location:** Puteaux, France (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, User Authentication, Cloud Storage, Customer Data Management, Data Architecture, Information Lifecycle Management, Metadata, Network Planning and Design, Application Data, Unstructured Data, Retrieval-Augmented Generation, Generative AI, Data Lakes, Storage Technologies, Information Technology, Low Latency, Data Analytics, Data Management, Model Inference, Data Pipelines
- **Published:** October 13, 2026
- **Apply:** https://hpe.wd5.myworkdayjobs.com/Jobsathpe/job/Puteaux-Hauts-de-Seine-France/Presales-Storage-Architect--Unstructured-Data---Expert-e--Avant-Vente-Architecte-H-F_1215052-2

## About the Role

* 7+ years of experience designing, implementing, or supporting enterprise storage and data architectures.

 * Bachelor's degree in Computer Science, Information Technology, Engineering, or 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.

 * Demonstrated ability to plan, configure, execute, and troubleshoot technical POCs.

 * Understanding of modern AI and analytics data pipelines, including AI inference, RAG, vector databases, data lakes/Lakehouse's, and large-scale analytics workloads.

## Description

We're seeking an experienced Storage Architect with strong expertise in unstructured data, AI and analytics workloads, and modern file and object storage architectures. This is a highly visible, customer-facing role with significant influence on solution design, customer adoption, and product strategy.

The ideal candidate combines deep storage fundamentals with a strong understanding of how data moves through modern AI and analytics environments. You will help customers design, size, validate, and optimize storage architectures supporting AI inference, Retrieval-Augmented Generation (RAG), analytics, data lakes, and other data-intensive workloads.

Role Overview:

As a Storage Architect - Unstructured Data, AI & Analytics, you will:

 * 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 the right storage architecture.

 * 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 (POCs).

 * Provide strong subject matter expertise in S3 object storage and foundational knowledge of NFS and SMB.

 * Apply knowledge of AI inference, RAG, 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.

 * Travel as needed to support customers, partners, and strategic opportunities., * 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 POCs validating performance, integration, scalability, and operational requirements.

 * Design storage architectures for AI inference, RAG, analytics, and data lake workloads, with consideration for 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 both executive and deeply technical audiences.

 * Support strategic presales engagements, RFIs/RFPs, solution sizing, and technical justification.