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) Model inference and deployment (Nice to have) Model training pipelines
Demonstrated ability to lead architecture from data requirements and access patterns rather than infrastructure-first design approaches
Map and optimize end-to-end data flow across the AI lifecycle, from ingestion through retrieval to model interaction and feedback loops
Proven experience working with Product Management and solution teams to define, develop, and extend AI Factory offerings, including: Contributing to reference architectures Influencing product directi
Experience sizing and designing GPU-based environments for AI workloads
Experience working with AI/ML or data engineering teams where data behavior, access patterns, and model interaction—not infrastructure alone—drive architectural decisions
Solid understanding of data architecture concepts, including: Data pipelines, data lakes, and object storage Performance considerations for large-scale data access
Demonstrated ability to evaluate and position solutions based on fit for purpose, including: Matching architectures to workload requirements and scale Understanding trade-offs across performance, cost
Proven ability to lead customer discovery and translate requirements into technical solutions
Strong communication skills with the ability to engage both technical and executive audiences
Full description
AI Data Platform Field ArchitectThis role has been designated as ‘Remote/Teleworker’, which means you will primarily work from home.Who We Are:
Hewlett 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.
Job Description:
We 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.
You 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.
A 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.
This 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.
Key Responsibilities
Data-Centric AI Architecture
Lead architecture discussions starting from data characteristics and lifecycle, including:
Data volume, velocity, and distribution
Structured vs. unstructured data considerations
Data locality, gravity, and movement patterns
Design AI solutions by optimizing:
Data access patterns (sequential vs. random, batch vs. real-time)
AI Data Platform Field Architect at Hewlett Packard Enterprise (Remote) — aijobsearch
AI pipelines for data movement efficiency, minimizing bottlenecks between storage, compute, and model layers Metadata, indexing, and retrieval efficiency (critical for RAG)
Recommend design optimizations and improvements for performance, cost efficiency, reliability, and trustworthiness.
Evaluate how data design decisions impact:
Model performance and accuracy
Latency (including time-to-first-token)
GPU utilization, ingest requirements, and cost efficiency
Customer Engagement & Deal Leadership
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
Serve as a trusted advisor to CTOs, Heads of AI, and Data Engineering leaders
Drive deal progression by aligning technical solutions to measurable business outcomes
Apply strong judgment in identifying where solutions are the right fit based on workload, scale, and requirements, ensuring credibility and long-term customer success
AI Solution Architecture & Sizing
Scope and size AI Factory environments based on:
GPU counts and configurations
Data volumes and throughput requirements
Model types and workloads (RAG, inference, training)
Define performance expectations across the full AI pipeline, including:
Data ingestion and preparation
Storage and retrieval patterns
GPU utilization and efficiency
Provide guidance on optimizing time-to-first-token (TTFT), throughput, and cost efficiency
Data & Storage Integration (X10K Focus)
Articulate the role of modern data platforms in AI workflows, including:
Object storage (S3) architectures
Data pipelines and pipeline simplification/elimination strategies
Integration with vector databases and AI frameworks
Position data platforms as a strategic enabler of AI performance, not just infrastructure
Align solution positioning to customer-specific data scale, access patterns, and performance needs
Cross-Functional Leadership
Partner closely with Product Management to:
Influence roadmap priorities across RAG, inference, and training
Provide structured field feedback on customer requirements, gaps, and competitive dynamics
Create and present high‑impact technical content (reference architectures, design patterns, whitepapers, conference talks, and internal/external publications) to influence customers, partners, and internal stakeholders.
Required Qualifications
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)
Model inference and deployment
(Nice to have) Model training pipelines
Demonstrated ability to lead architecture from data requirements and access patterns rather than infrastructure-first design approaches
Map and optimize end-to-end data flow across the AI lifecycle, from ingestion through retrieval to model interaction and feedback loops
Proven experience working with Product Management and solution teams to define, develop, and extend AI Factory offerings, including:
Contributing to reference architectures
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 where data behavior, access patterns, and model interaction—not infrastructure alone—drive architectural decisions
Solid understanding of data architecture concepts, including:
Data pipelines, data lakes, and object storage
Performance considerations for large-scale data access
Demonstrated ability to evaluate and position solutions based on fit for purpose, including:
Matching architectures to workload requirements and scale
Understanding trade-offs across performance, cost, and complexity
Proven ability to lead customer discovery and translate requirements into technical solutions
Strong communication skills with the ability to engage both technical and executive audiences
Preferred (Nice-to-Have) Experience
Exposure to high-performance computing (HPC) concepts or distributed compute environments
Familiarity with AI/ML frameworks and ecosystems (e.g., PyTorch, TensorFlow, vector databases)
Experience working with cloud and hybrid AI infrastructure
Background in storage technologies (object storage, high-throughput data platforms)
Experience collaborating with Product Management or influencing product strategy
What Success Looks Like
Consistently shaping and qualifying high-value AI Factory opportunities
Positioning solutions with precision—winning in the right opportunities for the right reasons
Enabling field teams to confidently position and sell AI solutions at scale
Driving measurable improvements in deal velocity, win rates, and pipeline growth
Influencing product direction based on real-world customer needs
Establishing a repeatable, scalable approach to AI Factory solution design
What We Can Offer You:Health & Wellbeing
We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.
Personal & Professional Development
We 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.
Unconditional Inclusion
We 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.
Let's Stay Connected:
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Job:
SalesJob Level:
TCP_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 This 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%."Information about employee benefits offered in the US can be found at
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