AI Data Platform Field Architect

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

📋 Description

• Facilitate discussions on data-centric AI architecture, focusing on data characteristics, lifecycle, volume, velocity, distribution, locality, and movement.

• Develop AI solutions that enhance data access patterns, pipeline efficiency, metadata management, indexing, and retrieval processes.

• Suggest improvements for performance, cost efficiency, reliability, and trustworthiness.

• Assess the influence of data design on model performance, latency, GPU utilization, ingestion requirements, and overall costs.

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

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

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

• Propel deal advancement by aligning technical solutions with quantifiable business results.

• Determine the scope and size of AI Factory environments based on GPU configurations, data volumes, throughput, model types, and workload characteristics.

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

• Direct the optimization of time-to-first-token, throughput, and cost efficiency.

• Clearly articulate and position object storage, data pipelines, vector database integrations, and AI frameworks as essential components for strategic AI enablement.

• Collaborate with Product Management to influence roadmap priorities and offer field insights.

• Produce and deliver technical content such as reference architectures, design patterns, whitepapers, conference presentations, and publications.

⛳️ Requirements

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

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

• Proven ability to lead architecture initiatives stemming from data requirements and access patterns.

• Capability to map and optimize the 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.

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

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

• Strong understanding of data pipelines, data lakes, and object storage solutions.

• Knowledge of performance considerations related to large-scale data access.

• Ability to evaluate and position solutions based on workload fit, scalability, performance, cost, and complexity.

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

• Excellent communication skills, with the ability to engage both technical and executive audiences.

• Preferred experience in HPC or distributed computing environments.

• Familiarity with PyTorch, TensorFlow, vector databases, cloud and hybrid AI infrastructure, and storage technologies is a plus.

🏝️ Benefits

• Comprehensive health and wellness benefits.

• Opportunities for personal and professional development.

• Flexible management of work and personal needs.

• Commitment to an equal opportunity and inclusive workplace.