If you're energized by solving complex systems challenges, excited to work alongside AI to amplify your impact, and motivated by the opportunity to shape what's next instead of simply maintaining what's been done before, you'll find your place here.
Join us and help build the future of enterprise technology.
From applied research to advanced engineering, the Engineering Technologist team has the expertise to shape ground-breaking products, material and processes. It’s a fascinating field of work. We’re involved in assessing the competition, developing technology and product strategies and generating intellectual property. We lead technology investigations, analyze industry capabilities and recommend potential acquisitions or vendor partner opportunities. Our insights influence product architecture and definitions. And we work with colleagues across the business to ensure our products always lead the way.
What you’ll achieve
Participate in the development of next-generation large-scale AI Infrastructure to include accelerated compute, AI Fabric and AI optimized storage. Engage with high profile AI customers to optimize solutions for their applications and tune systems for maximum performance. Drive innovation at datacenter level with liquid cooling technologies and power density.
Join us to do the best work of your career and make a profound social impact as a Storage Architect on our Engineering Technologist Team in London, United Kingdom
You will
Serve as the technical leader interfacing with enterprise customers to define architectures, understand workload requirements, and translate them into comprehensive solution designs. Architect AI-optimized storage and data management solutions integrating optimized, scale-out file, object, and parallel filesystem SDS technologies.‑optimized storage and data management solutions integrating scale‑out file, object, and parallel filesystem technologies
Influence end-to-end AI infrastructure stacks—from software frameworks through compute, storage, networking, data security, and datacenter deployment (L10–L12).‑to‑end AI infrastructure stacks—from software frameworks through compute, storage, networking, data security, and datacenter deployment (L10–L12)
Develop and propose solution configurations, BOMs, and SKUs based on customer needs in collaboration with Engineering and engage with strategic technology partners to co-innovate and build differentiated solutions.
Lead investigations new fabric technologies, and storage platforms to support large‑scale AI deployments. Serve as a technical escalation point for complex development challenges and represent Dell in internal and external architecture forums
Generate intellectual property, including invention disclosures and technology strategy insights and influence multi-year technology and product roadmaps with inputs from engineering, manufacturing, procurement, customers, and the broader industry.
- Take the first step towards your dream career
- Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role:
Essential Requirements
10+ years of experience in storage architecture, data platforms, or large-scale distributed systems. Expertise in scale-out file/object storage, parallel filesystems, and key storage concepts (NFS/S3, erasure coding, deduplication, encryption, tiering, backup, versioning).
Deep understanding of AI/ML workflows, data pipelines, training/inference patterns, Vector DB, KV Cache and enterprise cluster deployments and ability to collaborate with ISVs on data management and AI workflow integration.
Strong ability to define storage configurations to meet production grade performance and SLA requirements.‑grade performance and SLA requirements.
Excellent communication skills with experience presenting to cross functional teams and senior leaders.‑functional teams and senior leaders.
Demonstrated experience working with industry vendors to influence next generation technology design.‑generation technology design.
Ability to translate business outcomes into practical, scalable technical architectures; willingness to travel 20–30%.
Desirable Requirements
Knowledge of AI/ML or HPC performance engineering, including benchmarking and scripting (e.g., Python, Bash) on Linux and hands-on experience with datacenter technologies, including fabrics, cooling, telemetry, or cluster orchestration.
