AI Data Platform Field Architect

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

📋 Description

• Lead discussions on data-centric AI architecture by considering data characteristics, lifecycle, volume, velocity, distribution, locality, gravity, and movement patterns.

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

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

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

• Facilitate 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.

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

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

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

• Explain the roles of modern data platforms in AI workflows, encompassing S3 architectures, data pipelines, vector databases, and AI frameworks.

• Position data platforms as strategic enablers of AI performance.

• Collaborate with Product Management to shape roadmap priorities and provide structured feedback from the field.

• Develop and present technical content, including reference architectures, design patterns, whitepapers, conference talks, and publications.

⛳️ Requirements

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

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

• Capability to lead architecture discussions based on data requirements and access patterns.

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

• Experience in defining, developing, and expanding AI Factory offerings.

• Background in contributing to reference architectures and influencing product direction and roadmap priorities.

• Familiarity with sizing and designing GPU-based environments for AI workloads.

• Experience collaborating with AI/ML or data engineering teams.

• Knowledge of data pipelines, data lakes, object storage, and high-performance data access.

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

• Proven experience in customer discovery and technical solution translation.

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

• Preferred: exposure to HPC or distributed compute environments.

• Preferred: familiarity with PyTorch, TensorFlow, vector databases, and AI/ML ecosystems.

• Preferred: experience with cloud and hybrid AI infrastructure.

• Preferred: background in object storage and high-throughput data platforms.

• Preferred: experience working alongside Product Management or influencing product strategy.

🏝️ Benefits

• Comprehensive benefits that support physical, financial, and emotional well-being.

• Opportunities for personal and professional development.

• Flexible management of work and personal needs.

• An inclusive work environment.

• Employee benefits information is available for US employees.