{"id":1168655,"url":"https://alion.io/job/hewlett-packard-enterprise-ai-data-platform-field-architect","title":"AI Data Platform Field Architect","company":{"id":5292,"name":"Hewlett Packard Enterprise","domain":"hpe.com","url":"https://alion.io/company/hewlett-packard-enterprise","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":76,"open_postings":114,"ghost_share":0,"stale_share":0.956,"repost_share":0,"time_to_fill_p50_days":35,"computed_at":"2026-10-20T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":153500,"max":298500,"currency":"USD","period":"year","gross":null,"usd_annual":298500},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"RAG","optional":false},{"name":"HPC","optional":true},{"name":"PyTorch","optional":true},{"name":"TensorFlow","optional":true}],"status":"live","first_seen_at":"2026-09-01T00:00:00Z","employer_posted_date":"2026-09-01","last_verified_at":"2026-10-20T15:28:00Z","board_verified":true,"closed_at":null,"days_open":49,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":49},"description":"AI Data Platform Field ArchitectThis role has been designated as ‘Remote/Teleworker’, which means you will primarily work from home.Who We Are:\nHewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.\nJob Description:\nWe are seeking a highly strategic and technically grounded AI Data Platform Field CTO to help drive the next phase of growth for our X10K AI data platform business. This is a customer-facing architect role that leads with a data-first perspective, focusing on how data is created, moved, enriched, and consumed across AI pipelines, using infrastructure as an enabler rather than the starting point.\nYou will operate at the intersection of data architecture, AI infrastructure, and business value, partnering with customers and sales teams to design high-impact AI solutions spanning RAG, inference, and model training workflows. You will also act as a critical bridge between the field and Product Management, influencing roadmap priorities and helping build repeatable, scalable go-to-market motions.\nA key aspect of this role is the ability to work closely with sales and technical teams to identify and prioritize the right opportunities at the right time as we accelerate adoption in a rapidly evolving market. This includes applying strong technical and commercial judgment to align solutions with customer readiness, workload requirements, and scale, ensuring we win where we can deliver the most impact and long-term success.\nThis is not a pure storage role, but a strong understanding of how data platforms and storage enable AI pipelines is essential, along with the ability to position solutions thoughtfully based on where they deliver the most value.\nKey Responsibilities\nData-Centric AI Architecture\nLead architecture discussions starting from data characteristics and lifecycle, including:Data volume, velocity, and distribution\nStructured vs. unstructured data considerations\nData locality, gravity, and movement patterns\n\nDesign AI solutions by optimizing:Data access patterns (sequential vs. random, batch vs. real-time)\nAI pipelines for data movement efficiency, minimizing bottlenecks between storage, compute, and model layers Metadata, indexing, and retrieval efficiency (critical for RAG)\nRecommend design optimizations and improvements for performance, cost efficiency, reliability, and trustworthiness. \n\nEvaluate how data design decisions impact:Model performance and accuracy\nLatency (including time-to-first-token)\nGPU utilization, ingest requirements, and cost efficiency\n\nCustomer Engagement & Deal Leadership\nLead technical discovery sessions with enterprise customers to identify, shape, and qualify AI Factory opportunities\nTranslate business objectives into scalable AI architectures and solution designs\nServe as a trusted advisor to CTOs, Heads of AI, and Data Engineering leaders\nDrive deal progression by aligning technical solutions to measurable business outcomes\nApply strong judgment in identifying where solutions are the right fit based on workload, scale, and requirements, ensuring credibility and long-term customer success\nAI Solution Architecture & Sizing\nScope and size AI Factory environments based on:GPU counts and configurations\nData volumes and throughput requirements\nModel types and workloads (RAG, inference, training)\n\nDefine performance expectations across the full AI pipeline, including:Data ingestion and preparation\nStorage and retrieval patterns\nGPU utilization and efficiency\n\nProvide guidance on optimizing time-to-first-token (TTFT), throughput, and cost efficiency\nData & Storage Integration (X10K Focus)\nArticulate the role of modern data platforms in AI workflows, including:Object storage (S3) architectures\nData pipelines and pipeline simplification/elimination strategies\nIntegration with vector databases and AI frameworks\n\nPosition data platforms as a strategic enabler of AI performance, not just infrastructure\nAlign solution positioning to customer-specific data scale, access patterns, and performance needs\nCross-Functional Leadership\nPartner closely with Product Management to:Influence roadmap priorities across RAG, inference, and training\nProvide structured field feedback on customer requirements, gaps, and competitive dynamics\nCreate and present high-impact technical content (reference architectures, design patterns, whitepapers, conference talks, and internal/external publications) to influence customers, partners, and internal stakeholders. \n\nRequired Qualifications\n8+ years of experience in a technical presales, solutions architecture, or field CTO role\nStrong understanding of AI/ML workflows, including:Retrieval-Augmented Generation (RAG)\nModel inference and deployment\n(Nice to have) Model training pipelines\n\nDemonstrated ability to lead architecture from data requirements and access patterns rather than infrastructure-first design approaches\nMap and optimize end-to-end data flow across the AI lifecycle, from ingestion through retrieval to model interaction and feedback loops\nProven experience working with Product Management and solution teams to define, develop, and extend AI Factory offerings, including:Contributing to reference architectures\nInfluencing product direction and roadmap priorities\n\nExperience sizing and designing GPU-based environments for AI workloads\nExperience working with AI/ML or data engineering teams where data behavior, access patterns, and model interaction-not infrastructure alone-drive architectural decisions\nSolid understanding of data architecture concepts, including:Data pipelines, data lakes, and object storage\nPerformance considerations for large-scale data access\n\nDemonstrated ability to evaluate and position solutions based on fit for purpose, including:Matching architectures to workload requirements and scale\nUnderstanding trade-offs across performance, cost, and complexity\n\nProven ability to lead customer discovery and translate requirements into technical solutions\nStrong communication skills with the ability to engage both technical and executive audiences\nPreferred (Nice-to-Have) Experience\nExposure to high-performance computing (HPC) concepts or distributed compute environments\nFamiliarity with AI/ML frameworks and ecosystems (e.g., PyTorch, TensorFlow, vector databases)\nExperience working with cloud and hybrid AI infrastructure\nBackground in storage technologies (object storage, high-throughput data platforms)\nExperience collaborating with Product Management or influencing product strategy\nWhat Success Looks Like\nConsistently shaping and qualifying high-value AI Factory opportunities\nPositioning solutions with precision-winning in the right opportunities for the right reasons\nEnabling field teams to confidently position and sell AI solutions at scale\nDriving measurable improvements in deal velocity, win rates, and pipeline growth\nInfluencing product direction based on real-world customer needs\nEstablishing a repeatable, scalable approach to AI Factory solution design\nWhat We Can Offer You:\nHealth & Wellbeing\nWe strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.\nPersonal & Professional Development\nWe also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have - whether you want to become a knowledge expert in your field or apply your skills to another division.\nUnconditional Inclusion\nWe are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.\nLet's Stay Connected:\nFollow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.\nJob:\nSalesJob Level:\nTCP_04\"The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.- United States of America: Annual Salary USD 153,500 - 298,500 in Colorado // 146,000 - 343,000 in Arizona & Nevada & New Jersey & Texas\nThis range reflects the minimum to maximum combined base and target-level sales compensation that would be paid if the hire performs at 100% of their sales plan. Of that on-target pay amount, the mix of base salary and target-level sales compensation is 80%/20%.\"\nInformation about employee benefits offered in the US can be found at https://myhperewards.com/main/new-hire-enrollment.html\nThe estimated job application period closure is October 31 2026; this timeline is provided for transparency and internal planning purposes.HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBTemployer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.\nHewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.\nHPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.\nRecruitment Fraud Alert\nWe have become aware of an increase in fraudulent recruitment activities in which individuals impersonate our company or authorized recruitment agencies to offer fake employment opportunities. These scams may occur through false websites, emails, social media, or chat-based applications and often aim to obtain personal information or money. Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge a candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. We also never request personal information such as back account details, Social Security numbers, or national IDs via social media or chat applications.\nAll legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any third party claiming to represent the company. Any reliance on fraudulent communication is at the individual’s own risk, and HPE disclaims legal liability for any resulting damages. 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