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.
Key Responsibilities
- 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.
Required Qualifications
- 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.
- Ability to discuss storage within the broader 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.
- Excellent communication, presentation, troubleshooting, and problem-solving skills.
- Willingness and ability to travel for customer engagements.
AI & Analytics Skills
Strong candidates will have experience with several of the following:
- AI inference and RAG architectures
- Vector databases, embeddings, and retrieval workflows
- Data lakes 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
- Performance characterization and workload benchmarking
Storage Technologies & Platforms
Experience with one or more enterprise file or object storage platforms is preferred, including:
- Dell PowerScale / ObjectScale
- Pure Storage FlashBlade
- NetApp ONTAP / StorageGRID
- VAST Data
- Scality
- Other enterprise file or S3-compatible object storage platforms
Cloud & Competitive Skills
Strong pluses include:
- Familiarity with AWS, Azure, and GCP storage services and integration patterns.
- Understanding of hybrid and multi-cloud data architectures.
- Knowledge of modern AI and analytics platforms and their storage requirements.
- Strong awareness of the competitive enterprise file and object storage landscape.
- Experience in technical presales, consulting, solution architecture, or customer advisory roles.