[Hiring] AI Data Platform Field Architect @Hewlett Packard Enterprise

Role 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.

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

Requirements

• 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 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
• 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
• 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
• 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
• 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.

Benefits

• Health & Wellbeing: Comprehensive suite of benefits that supports physical, financial, and emotional wellbeing.
• Personal & Professional Development: Specific programs catered to helping you reach any career goals you have.
• Unconditional Inclusion: We celebrate individual uniqueness and provide flexibility to manage work and personal needs.