
10,000+ employees
đ˘ Enterprise
đ§ Hardware
đ¤ Artificial Intelligence
đ° $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 companyâs offerings â reflected in the provided text â 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.
đĽ 0 minutes ago
đ Florida, Illinois, +3 more states â Remote
đľ $128.8k - $302.4k / year
â° Full Time
đ Senior
đ´ Lead
đ° Data Engineer
đŚ H1B Visa Sponsor
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10,000+ employees
đ˘ Enterprise
đ§ Hardware
đ¤ Artificial Intelligence
đ° $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 companyâs offerings â reflected in the provided text â 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 and lifecycle ⢠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, and workloads ⢠Define performance expectations across data ingestion, storage, retrieval, and GPU utilization ⢠Guide optimization of time-to-first-token, throughput, and cost efficiency ⢠Articulate and position modern data platforms, object storage, data pipelines, vector database, and AI framework integrations ⢠Partner with Product Management to influence roadmap priorities and provide structured field feedback ⢠Create and present technical content including reference architectures, design patterns, whitepapers, conference talks, and publications
⢠8+ years of experience in a technical presales, solutions architecture, or field CTO role ⢠Strong understanding of AI/ML workflows, including Retrieval-Augmented Generation (RAG) and model inference and deployment ⢠Demonstrated 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 fit for purpose ⢠Ability to match architectures to workload requirements and scale ⢠Understanding of trade-offs across performance, cost, and complexity ⢠Proven ability to lead customer discovery and translate requirements into technical solutions ⢠Strong communication skills engaging technical and executive audiences ⢠U.S. work location in Florida, Illinois, North Carolina, Texas, or Virginia
⢠Comprehensive suite of benefits supporting physical, financial, and emotional wellbeing ⢠Health and wellbeing benefits ⢠Personal and professional development programs ⢠Flexible work and personal needs management ⢠Inclusive workplace and equal employment opportunity
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