AI Data Platform Field Architect

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

📋 Description

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

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

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

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

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

• 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 outcomes.

• Determine the scope and size of AI Factory environments considering GPU configurations, data volumes, throughput, model types, and workloads.

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

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

• Clearly communicate the roles of modern data platforms within AI workflows, encompassing S3 object storage, data pipelines, vector databases, and AI frameworks.

• Position data platforms as key enablers of AI performance.

• Collaborate with Product Management to influence roadmap priorities and offer structured feedback from the field.

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

⛳️ Requirements

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

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

• Proven capability to lead architecture based on data requirements and access patterns, rather than an infrastructure-first approach.

• Ability to map and optimize the complete data flow throughout the AI lifecycle.

• Demonstrated experience collaborating with Product Management and solution teams to define, develop, and enhance AI Factory offerings.

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

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

• Strong grasp of data architecture concepts, including data pipelines, data lakes, and object storage.

• Knowledge of performance considerations for large-scale data access.

• Ability to assess and position solutions based on their appropriateness for specific purposes.

• Proven track record in leading customer discovery and translating requirements into technical solutions.

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

• Preferably experienced with high-performance computing (HPC) concepts or distributed computing environments.

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

• Experience with cloud and hybrid AI infrastructure is advantageous.

• A background in storage technologies is preferred.

🏝️ Benefits

• A comprehensive range of health and wellbeing benefits that support physical, financial, and emotional wellness.

• Opportunities for personal and professional development programs.

• Flexible management of work and personal needs.

• An inclusive workplace culture.

• Sales compensation opportunity based on target-level compensation.