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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Technical Solutions Architect - AI Platforms & Architecture - **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, File Systems, Meta-Data Management, NetApp Applications, Data ONTAP (Server Appliance), Weka, Scripting, Performance Testing, Data Ingestion, Apache Spark, Data Strategy, Data Lakes, AI Platforms, Dask, Apache Kafka, Apache Nifi, Data Management, Slurm, Machine Learning Operations, Data Pipelines - **Published:** July 1, 2026 - **Apply:** https://www.clearancejobs.com/jobs/9008327/technical-solutions-architect-ai-platforms-architecture ## About the Role 5+ years of experience in enterprise storage and data platform solutions, with demonstrated ability to both assess technical fit and advise customers on AI data readiness strategy, including: Storage & Data Infrastructure * Deep working knowledge of high-performance parallel file systems * Strong familiarity with enterprise NAS and object storage platforms * Ability to evaluate storage platform fit against AI workload requirements, including training, checkpointing, and inference, without necessarily performing the hardware sizing or implementation NVIDIA AI Data Platform * Working knowledge of NVIDIA AI Data Platform design requirements, reference architectures, and validation frameworks * Understanding of GPU-Direct Storage, NVAIE, and Mission Control as capabilities, with the ability to articulate their value and applicability to customer AI use cases * Familiarity with how AIDP-validated storage platforms integrate with NVIDIA compute architectures including DGX, HGX, MGX, and OVX Data Pipelines & Frameworks * Working knowledge of data pipeline patterns and orchestration tools including Apache Spark, Ray, Dask , and Apache Airflow, sufficient to advise on design fit and architectural trade-offs * Understanding of data lakehouse and data fabric concepts including Delta Lake, Apache Iceberg, Apache Hudi, and Unity Catalog * Familiarity with data ingestion and movement tools such as Apache Kafka, Apache NiFi , and Airbyte Professional Skills * Demonstrated ability to engage executive and technical audiences with equal fluency * Experience delivering advisory workshops, architecture presentations, and strategic recommendations to enterprise customers * Strong written communication skills; capable of producing thought leadership content, briefings, and reference architectures * Sound organizational skills and ability to manage multiple concurrent customer engagements 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, working closely with our strategic ecosystem partner 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 the Everpure partner program . Responsibilities * Advise customers on AI Data Readiness strategy, assessing current data infrastructure, pipeline maturity, and platform capabilities against the requirements of their targeted AI use cases * Translate NVIDIA AI Data Platform features, including GPU-Direct Storage, NVAIE, and Mission Control, into tangible business and workload outcomes for enterprise customers and field audiences * Develop and deliver AI Data Readiness workshops, assessments, and frameworks that help customers identify gaps between their current data environment and the requirements of production AI * Guide customers on how AIDP-validated platforms such as VAST, Weka, Dell PowerScale , and NetApp ONTAP AI enable specific AI use cases across training, inference, and MLOps workflows * Partner with HPA and infrastructure architects to provide advisory context on how data strategy, pipeline design, and platform selection affect AI Factory outcomes at the customer level * Develop use case guidance on how data pipeline and framework design choices, including orchestration, transformation, and ingestion patterns, affect AI workload performance and data readiness * Create enablement content, including briefings, workshops, reference architectures, and thought leadership, that equips WWT field teams to confidently position AIDP value in customer conversations * Support field teams with deal-level advisory, translating AIDP platform capabilities into business justification and customer outcomes * Maintain current knowledge of AIDP roadmap, certifications, and partner program requirements to ensure WWT's advisory position reflects the latest capabilities * Participate in AI and Data Team meetings, partner briefings, and training to remain aligned across the practice * Travel as required to customer sites, partner events, and WWT facilities Travel Requirements: 25-50%, 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 - [Running Secure Life Science Research at Scale using Hybrid GPU HPC and Kubernetes 🧬](https://www.wearedevelopers.com/videos/100355-running-secure-life-science-research-at-scale-using-hybrid-gpu-hpc-and-kubernetes) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Reference Architecture of AI in the Cloud](https://www.wearedevelopers.com/videos/1613-reference-architecture-of-ai-in-the-cloud) - [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) ## 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) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)