AI Data Platform Architect

🕒 il y a 1 mois

🌵 Arizona, Colorado, +3 états de plus – Distant

🌵 Arizona – Remote ⛰️ Colorado – Remote 🎰 Nevada – Remote 🏖️ New Jersey – Remote 🤠 Texas – Remote

💵 $116 800 - $274 400 / an

⏰ Temps Plein

🟠 Senior

🔴 Expert

🔙 Ingénieur Back-end

🦅 Parrain de Visa H1B

Cette entreprise a parrainé des visas H1B par le passé.

👻 Score fantôme 8%

Ce que ça veut dire : la probabilité que personne ne recrute vraiment pour cette offre.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

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Hewlett Packard Enterprise

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10 000+ employés

🏢 Entreprise

🔧 Matériel

🤖 Intelligence artificielle

💰 €1 500 000 000 Post-IPO Equity - Hewlett Packard Enterprise en 2025-04

Enterprise • Hardware • Artificial Intelligence

Hewlett Packard Enterprise est un leader mondial de la technologie, fournissant des solutions informatiques innovantes pour renforcer les entreprises. HPE propose un portefeuille complet de produits et services, y compris la plateforme HPE GreenLake edge-to-cloud qui offre une expérience de cloud hybride permettant aux entreprises de gérer les charges de travail à travers les clouds privés et publics de manière transparente. De plus, l'entreprise se spécialise dans le calcul haute performance, les solutions de réseau et de stockage, ainsi que dans les capacités d'IA et d'analyse des données pour stimuler la productivité et l'efficacité opérationnelle. HPE s'engage à aider les organisations à améliorer leurs transformations numériques tout en sécurisant les données et optimisant l'infrastructure informatique.

Description

• Lead data-centric AI architecture discussions based on data characteristics, lifecycle, volume, velocity, distribution, locality, gravity, and movement patterns • 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 efficiency • 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 using GPU configurations, data volumes, throughput, model types, and workloads • Define performance expectations across data ingestion, preparation, storage, retrieval, and GPU utilization • Guide optimization of time-to-first-token, throughput, and cost efficiency • Articulate and position X10K data platforms, object storage, data pipelines, vector database integrations, and AI frameworks • 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 • Shape and qualify high-value opportunities, enable field teams, improve deal velocity and win rates, grow pipeline, and establish repeatable AI Factory solution design

🎯 Exigences

• 8+ years of experience in technical presales, solutions architecture, or a field CTO role • 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 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 • Solid understanding of data pipelines, data lakes, object storage, and large-scale data access performance • Ability to evaluate and position solutions based on workload requirements, scale, performance, cost, and complexity • Proven ability to lead customer discovery and translate requirements into technical solutions • Strong communication skills engaging technical and executive audiences • Exposure to HPC concepts or distributed compute environments (preferred) • Familiarity with AI/ML frameworks and ecosystems such as PyTorch, TensorFlow, and vector databases (preferred) • Experience with cloud and hybrid AI infrastructure (preferred) • Background in storage technologies (preferred) • Experience collaborating with Product Management or influencing product strategy (preferred)

🏖️ Avantages

• Comprehensive suite of benefits supporting physical, financial, and emotional wellbeing • Personal and professional development programs • Flexible work and personal needs management • Inclusive workplace and individual uniqueness celebrated • Employee benefits information provided through HPE Rewards

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