AI Data Platform Architect

This is a fully remote position, open to applicants in Arizona, +4 more states.

📋 Description

• Facilitate discussions on data-centric AI architecture based on factors such as data characteristics, lifecycle, volume, velocity, distribution, locality, gravity, and movement patterns.

• Create AI solutions that optimize data access patterns, enhance AI pipeline data movement, and improve metadata, indexing, and retrieval efficiency.

• Suggest performance optimizations that enhance cost efficiency, reliability, and trustworthiness.

• Assess the effects of data design on model performance, latency, GPU utilization, ingest requirements, and cost efficiency.

• Lead technical discovery sessions with enterprise clients to identify, shape, and qualify AI Factory opportunities.

• Convert business goals into scalable AI architectures and solution designs.

• Provide guidance to CTOs, Heads of AI, and Data Engineering leaders.

• Propel deal progression by aligning technical solutions with quantifiable business outcomes.

• Evaluate and size AI Factory environments based on GPU configurations, data volumes, throughput, model types, and workloads.

• Establish performance expectations for data ingestion, preparation, storage, retrieval, and GPU utilization.

• Assist in optimizing time-to-first-token, throughput, and cost efficiency.

• Clearly articulate and position X10K data platforms, object storage, data pipelines, vector database integrations, and AI frameworks.

• Collaborate with Product Management to shape roadmap priorities and deliver structured field feedback.

• Develop and present technical materials such as reference architectures, design patterns, whitepapers, conference presentations, and publications.

• Identify and qualify high-value opportunities, enable field teams, enhance deal velocity and win rates, grow the pipeline, and establish repeatable AI Factory solution designs.

⛳️ Requirements

• Over 8 years of experience in technical presales, solutions architecture, or a field CTO capacity.

• Deep understanding of AI/ML workflows, including Retrieval-Augmented Generation (RAG) and model inference and deployment.

• Capability to lead architecture from data requirements and access patterns rather than adopting an infrastructure-first approach.

• Proficiency in mapping and optimizing end-to-end data flow throughout the AI lifecycle.

• Experience in defining, developing, and enhancing AI Factory offerings alongside Product Management and solution teams.

• Proven track record of contributing to reference architectures and influencing product direction and roadmap priorities.

• Experience in sizing and designing GPU-based environments for AI workloads.

• Background working with AI/ML or data engineering teams.

• Solid grasp of data pipelines, data lakes, object storage, and large-scale data access performance.

• Ability to assess and position solutions based on workload requirements, scale, performance, cost, and complexity.

• Demonstrated capability to lead customer discovery sessions and translate requirements into technical solutions.

• Excellent communication skills for engaging both technical and executive audiences.

• Exposure to HPC concepts or distributed computing environments is preferred.

• Familiarity with AI/ML frameworks and ecosystems such as PyTorch, TensorFlow, and vector databases is preferred.

• Experience with cloud and hybrid AI infrastructure is preferred.

• Background in storage technologies is preferred.

• Experience collaborating with Product Management or influencing product strategy is preferred.

🏝️ Benefits

• A comprehensive array of benefits that support physical, financial, and emotional well-being.

• Programs for personal and professional development.

• Flexible work arrangements to accommodate personal needs.

• An inclusive workplace that celebrates individual uniqueness.

• Employee benefits information accessible through HPE Rewards.