Job DescriptionStaff Technologist-AI ArchitectInfrastructure Solutions Group (ISG) builds the products that power infrastructure, solutions, and data management our customers need most. Our teams design and develop the hardware and software that connect infrastructure, accelerate computational workloads, integrate across the stack, protect data continuity, and deliver the platforms, applications, and diagnostics our customers rely on every day at enterprise scale.
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.
Join us as a
Staff Technologist-AI Architect on our
ISG-CTOteam in
Santa Clara, California to do the best work of your career and make a profound social impact.
What you'll achieveAs a
Staff Technologist-AI Architect, you will architect Dell's next-generation AI Architecture (including the Dell AI Factory) by driving the empirical characterization, performance modeling, and full-stack integration of frontier AI models and autonomous agentic systems. You will evaluate cutting-edge model architectures, build automated performance benchmarking harnesses across diverse accelerators, and design turnkey production architectures bridging Kubernetes, low-latency inference runtimes, enterprise data platforms, and confidential hardware fabrics.
You will:- Architect Dell's Next-Gen AI Architectures: Drive end-to-end reference architectures and system-level validation for enterprise-scale AI platforms (e.g., Dell AI Factory, rack-scale IR7000/IR9100 liquid-cooled systems, and modular HGX/NVLink clusters).
- Frontier Model Characterization & Trend Tracking: Track, evaluate, and characterize emerging frontier model architectures and reasoning paradigms (e.g., dense Transformers, large-scale Mixture-of-Experts like DeepSeek-V3/V4 and Llama 4 Scout, hybrid attention, and native multimodal models).
- Hands-On Deployment & Performance Benchmarking: Design and automate hands-on benchmarking pipelines to rigorously measure critical inference metrics across real-world workloads (e.g., profiling Time to First Token [TTFT], Inter-Token Latency [ITL], prefill/decode disaggregation, KV-cache memory offload, and FP8/FP4 quantization).
- Agentic Frameworks & Multi-Agent Systems: Understand and design for autonomous, multi-step agentic execution patterns, tool calling, and execution loops (e.g.NVIDIA OpenShell sandboxes).
- Data & Context Layer for AI: Integrate high-throughput data pipelines and context-grounding platforms to eliminate ETL and prevent hallucinations (e.g., Dell AI Data Platform [AIDP], Starburst/Trino federated SQL, Apache Spark, Elasticsearch vector indexing, and RAG architectures).
Take the first step towards your dream careerEvery Dell Technologies team member brings something unique to the table. Here's what we are looking for with this role:
Essential Requirements- Deep technical understanding of GPU architectures and emerging alternate accelerators to match model workloads to optimal hardware.
- Experience with Production Storage & High-Speed Data Fabrics: Architect high-throughput, low-latency data and network fabrics essential for continuous AI pipelines (e.g., Dell PowerScale all-flash NFS with GPUDirect Storage [GDS], Dell ObjectScale S3, RoCEv2/Spectrum-X Ethernet, and InfiniBand).
- Experience designing Confidential Computing & Enterprise Security: Implement hardware-anchored zero-trust security and data-in-use protection for sensitive enterprise models and regulated data (e.g., NVIDIA Confidential Computing, AMD SEV-SNP, Intel TDX, and SPIFFE/mTLS attestation).
- Inference Serving Engines & Ecosystem Mastery: Deploy, optimize, and evaluate production-grade inference serving frameworks (e.g., vLLM, TensorRT-LLM, SGLang, and Triton Inference Server).
- Enterprise Kubernetes & Infrastructure Orchestration: Architect resilient containerized AI environments utilizing modern Kubernetes platforms, operators, and schedulers (e.g., Red Hat OpenShift, Kubernetes Gateway API, NVIDIA GPU Operator, and Run:ai).
Desirable Requirements- 15+ years of professional experience with a Bachelor's degree or equivalent experience in Engineering (Advanced degree highly preferred)
- Ability to travel and to assess customer requirements, develop blueprint based on the customer's geographical area with strong verbal and written communication skills along with customer and partner project/program leadership experience