AI Data Platform Field Architect

🔥 2 minutes ago

🐊 Florida, Illinois, +3 more states – Remote

🐊 Florida – Remote 🌽 Illinois – Remote 🌲 North Carolina – Remote 🤠 Texas – Remote ⚔️ Virginia – Remote

💵 $128.8k - $302.4k / year

⏰ Full Time

🟠 Senior

🔴 Lead

🚰 Data Engineer

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Hewlett Packard Enterprise

WebsiteLinkedInAll Job Openings

10,000+ employees

🏢 Enterprise

🔧 Hardware

🤖 Artificial Intelligence

💰 $1.5G Post-IPO Equity - Hewlett Packard Enterprise on 2025-04

Enterprise • Hardware • Artificial Intelligence

Hewlett Packard Enterprise is an enterprise-focused technology company that delivers infrastructure, software, and services to help organizations build, manage, and secure hybrid cloud and AI-enabled environments. The company’s offerings — reflected in the provided text — include servers and high-performance computing (HPE ProLiant, HPE Cray), enterprise storage (HPE Alletra), networking products and services (HPE Aruba, Juniper partnership), AI platforms and turnkey AI factories, hybrid cloud and as-a-service offerings (GreenLake), security and networking (Zero Trust, SASE), and a broad portfolio of professional, advisory, and support services. HPE positions itself as a partner for large organizations modernizing data centers, deploying AI at scale, and adopting hybrid cloud operations.

📋 Description

• Lead data-centric AI architecture discussions focused on data characteristics, lifecycle, volume, velocity, distribution, locality, and movement • Design AI solutions optimizing data access patterns, AI pipeline data movement, metadata, indexing, and retrieval efficiency • Recommend optimizations for performance, cost efficiency, reliability, and trustworthiness • Evaluate impacts of data design on model performance, latency, GPU utilization, ingest requirements, and cost • Lead technical discovery sessions with enterprise customers to identify, shape, and qualify AI Factory opportunities • Translate business objectives into scalable AI architectures and solution designs • Advise CTOs, Heads of AI, and Data Engineering leaders • Drive deal progression by aligning technical solutions with measurable business outcomes • Scope and size AI Factory environments based on GPU configurations, data volumes, throughput, model types, and workloads • Define performance expectations for ingestion, preparation, storage, retrieval, and GPU utilization • Guide optimization of time-to-first-token, throughput, and cost efficiency • Articulate modern data platform roles in AI workflows, including S3 object storage, data pipelines, vector databases, and AI frameworks • Position data platforms as strategic AI performance enablers and align solutions to customer needs • Partner with Product Management to influence roadmap priorities and provide field feedback • Create and present technical content including reference architectures, design patterns, whitepapers, conference talks, and publications

🎯 Requirements

• 8+ years of experience in technical presales, solutions architecture, or field CTO roles • Strong understanding of AI/ML workflows, including Retrieval-Augmented Generation (RAG) and model inference/deployment • Ability to lead architecture from data requirements and access patterns rather than infrastructure-first approaches • Ability to map and optimize end-to-end data flow across the AI lifecycle • Experience defining, developing, and extending AI Factory offerings with Product Management and solution teams • Experience contributing to reference architectures and influencing product direction and roadmap priorities • Experience sizing and designing GPU-based environments for AI workloads • Experience working with AI/ML or data engineering teams • Understanding of data pipelines, data lakes, object storage, and large-scale data access performance • Ability to match architectures to workload requirements and scale and evaluate performance, cost, and complexity trade-offs • Proven ability to lead customer discovery and translate requirements into technical solutions • Strong communication skills engaging technical and executive audiences • Preferred/nice-to-have: HPC or distributed compute exposure; familiarity with PyTorch, TensorFlow, vector databases; cloud and hybrid AI infrastructure; storage technologies; Product Management collaboration

🏖️ Benefits

• Comprehensive health and wellbeing benefits supporting physical, financial and emotional wellbeing • Personal and professional development programs • Flexible work and personal needs management • Inclusive workplace culture • Employee benefits information provided through HPE Rewards