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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Technical Solutions Architect - AI Storage & Data Platforms - **Company:** World Wide Technology - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $125,000.0 - $156,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon S3, Apache HTTP Server, Cloud Storage, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Software Design Patterns, File Systems, General Parallel File Systems, Meta-Data Management, NetApp Applications, Data ONTAP (Server Appliance), Weka, Scripting, Performance Testing, Data Ingestion, Apache Spark, Data Layers, Microsoft Fabric, Data Lakes, Kubernetes, StorageGrid, Dask, Apache Kafka, Apache Nifi, Data Management, Slurm, Machine Learning Operations, Data Lakehouse, Isilon, Data Pipelines, Nvme - **Published:** July 1, 2026 - **Apply:** https://www.clearancejobs.com/jobs/9005655/technical-solutions-architect-ai-storage-data-platforms ## About the Role 5+ years of experience architecting, implementing, selling, or marketing enterprise storage and data platform solutions, with a strong focus on AI/ML infrastructure, including: Storage & Data Infrastructure * High-performance parallel file systems: VAST Data Platform, Weka Data Platform, DDN EXAScaler / AI400, IBM GPFS / Spectrum Scale, Lustre * Enterprise NAS and object storage: NetApp ONTAP AI, StorageGRID , Dell PowerScale (Isilon), Dell ECS / ObjectScale , Dell PowerStore * Storage sizing and performance modeling for AI training, checkpointing, and inference workloads NVIDIA AI Data Platform * Familiarity with NVIDIA AI Data Platform design requirements, reference architectures, and validation frameworks * Experience with NVIDIA GPU-Direct Storage, NVAIE, Mission Control, and related software ecosystem components * Understanding of how storage and data platforms integrate with NVIDIA DGX, HGX, MGX, and OVX compute architectures Data Pipelines & Frameworks * Data pipeline design and orchestration using Apache Spark, Ray, Dask , Apache Airflow, and/or Prefect * Data lakehouse and data fabric concepts: Delta Lake, Apache Iceberg, Apache Hudi, Unity Catalog * Data ingestion, transformation, and movement tools (e.g., Apache Kafka, Apache NiFi , Airbyte ) Professional Skills * Demonstrated ability to engage executive and technical audiences with equal fluency * Strong written and verbal communication skills; experience delivering architecture presentations and technical proposals * Sound organizational, conflict resolution, time management, and negotiation skills Nice to Have * Python scripting for data pipeline automation or storage performance testing * Experience with NVIDIA Run:ai , Slurm , or other workload schedulers as they relate to storage I/O optimization * Previous exposure to NVIDIA Enterprise and NCP reference architectures * Experience with cloud storage integration: AWS S3, Azure Blob, Google Cloud Storage, and hybrid data fabric designs * Familiarity with data governance, data cataloging, and compliance frameworks in AI environments ## Description Partner Solution Development Serve as WWT's technical lead for our storage and data platform partner ecosystem, including NetApp, VAST Data, Weka, DDN, Dell ( PowerStore , PowerScale , ECS, ObjectScale ), and Everpure . Develop and maintain joint solution designs, reference architectures, and go-to-market plays. Pre-Sales & Customer Engagement Engage directly with customers to assess AI data infrastructure requirements, define architectures, and deliver compelling solution proposals - including HLDs, BOMs, and LLDs - for enterprise and hyperscale AI workloads. Field Enablement & Thought Leadership Develop and deliver training, briefings, workshops, and reference architectures that enable WWT's field teams and partners to position and sell AI storage and data platform solutions with confidence. Pipeline & Business Development Collaborate with regional architects, sales leadership, and the broader GS&A practice to identify , qualify, and advance new business opportunities in the AI data infrastructure space. Practice & Partner Alignment Maintain OEM and partner certifications, track product roadmaps, and align WWT's go-to-market strategy with partner initiatives - including NVIDIA AI Data Platform certifications and NetApp, VAST, Weka, and DDN partner programs. Responsibilities * Architect high-performance storage and data platform solutions for AI/ML workloads, aligned to NVIDIA AI Data Platform design patterns and partner-validated reference architectures * Design and size parallel file system, object storage, NVMe-oF , and GPU-Direct Storage (GDS) environments based on model type, dataset scale, and customer use case * Develop data pipeline and data framework architectures supporting AI training, inference, and MLOps workflows - leveraging tools such as Apache Spark, Ray, Dask , Airflow, MLflow , and Kubeflow * Define data lakehouse and data fabric architectures using platforms such as NetApp ONTAP AI, VAST Data Platform, Weka Data Platform, DDN EXAScaler /AI400, and Dell PowerScale /ECS * Collaborate with HPA compute and networking architects to deliver integrated AI Factory designs across compute, storage, networking, and data layers * Assist customers with GPU-Direct Storage adoption, NVMe-oF fabric design, and data movement optimization for GPU-accelerated training and inference * Deliver market scans, competitive analysis, and solution comparisons across WWT's AI storage and data platform portfolio * Support field teams with deal-level technical assistance including architecture reviews, sizing guidance, and customer presentations * Drive partner roadmap alignment and co-sell motions with NetApp, VAST Data, Weka, DDN, Dell, Everpure , and NVIDIA * Develop enablement materials including brochures, briefings, workshops, reference architectures, and demos * Participate in regular HPA team meetings, partner briefings, and training sessions * Travel as required to customer sites, partner events, and WWT facilities, We strive to create an environment where all employees are empowered to succeed based on their skills, performance, and dedication. Our goal is to cultivate a culture of belonging that encourages innovation, collaboration, and respect for all team members, ensuring that WWT remains a great place to work for All! ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [AI That Fits Your Business, Not the Other Way Around](https://www.wearedevelopers.com/videos/100148-ai-that-fits-your-business-not-the-other-way-around) - [Reference Architecture of AI in the Cloud](https://www.wearedevelopers.com/videos/1613-reference-architecture-of-ai-in-the-cloud) ## Related Articles - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)