
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.
🔥 1 hour ago
🌵 Arizona, Colorado, +3 more states – Remote
💵 $116.8k - $274.4k / year
⏰ Full Time
🟠 Senior
🔴 Lead
🚰 Data Engineer
🦅 H1B Visa Sponsor
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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.
• Lead data-centric AI architecture discussions based on data characteristics, lifecycle, volume, velocity, distribution, locality, and movement • Design AI solutions optimizing data access patterns, pipeline efficiency, metadata, indexing, and retrieval • 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, GPU utilization, and efficiency • Guide optimization of time-to-first-token, throughput, and cost efficiency • Articulate and position object storage, data pipelines, vector database integrations, and AI frameworks as strategic AI enablers • 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
• 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 and deployment • Ability to lead architecture from data requirements and access patterns • Ability to map and optimize end-to-end data flow across the AI lifecycle • Experience defining, developing, and extending AI Factory offerings • 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 • Solid understanding of data pipelines, data lakes, and object storage • Understanding of performance considerations for large-scale data access • Ability to evaluate and position solutions based on workload fit, scale, performance, cost, and complexity • Proven ability to lead customer discovery and translate requirements into technical solutions • Strong communication skills with technical and executive audiences • Exposure to HPC or distributed compute environments preferred • Familiarity with PyTorch, TensorFlow, vector databases, cloud and hybrid AI infrastructure, and storage technologies preferred
• Comprehensive health and wellbeing benefits • Personal and professional development programs • Flexible work and personal needs management • Equal opportunity and inclusive workplace
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