Senior Solutions Architect, Data Platform GTM

NVIDIA is seeking outstanding AI Solutions Architects to assist and support customers that are building solutions with our newest AI technology.

This role will focus on helping ISVs understand, adopt, and commercialize NVIDIA acceleration technologies across structured data processing, analytics, unstructured data, retrieval, and agentic AI workflows.

Responsibilities:

• Drive technical GTM with Data Platform ISVs across query engines, databases, analytics platforms, data processing frameworks, and AI data infrastructure.
• Partner with ISVs on discovery, architecture reviews, technical deep dives, POCs, benchmarks, demos, and customer-facing enablement.
• Help ISVs identify the right NVIDIA acceleration paths for their platforms and use cases, including cuDF, Spark RAPIDS, Polars, Velox, cuVS, and related NVIDIA libraries.
• Build repeatable GTM assets such as reference architectures, technical playbooks, demos, blogs, talks, and customer training.
• Support emerging data platform use cases for GenAI, including unstructured data processing, RAG pipelines, data preparation, and retrieval workflows.
• Travel up to 20% for conferences and customers may be required.

Requirements:

• BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience).
• 8+ years of hands-on experience with Machine Learning, Deep Learning and Data Analytics.
• Strong background in data platforms, distributed systems, analytics, databases, or systems for managing and processing data.
• Familiarity with data ecosystems such as Spark, Pandas, Polars, DuckDB, Trino, Presto, Velox, vector databases, or unstructured data pipelines.
• Experience working with ISVs, partners, or enterprise customers in a solutions architecture or field engineering role.
• Excellent presentation, communication and collaboration skills.

Preferred Qualifications:

• Hands-on experience with NVIDIA GPUs and software libraries, such as NeMo Retriever, cuVS, RAPIDS and cuDF.
• Background in RAG, agentic AI, unstructured data processing, or inference and data platform integration.
• Excellent C/C++ programming skills, including debugging, profiling, code optimization, performance analysis, and test design.
• Familiarity with parallel programming and distributed computing platforms.

You will also be eligible for equity and benefits.