Senior Solutions Architect, Data Platform GTM
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Get Started FreeAbout interviewing at NVIDIA
Recruiter screen, a technical screen mixing resume deep-dive with live coding, a hiring-manager conversation, then a panel of three to five 45–60 minute rounds: coding, systems design under hardware constraints, a domain deep-dive, and behavioral. Highly team-specific — you interview directly with the team — with C++ depth expected almost universally and decisions sometimes taking five-plus weeks after the panel.
Read the full NVIDIA interview process →Description
NVIDIA is seeking outstanding AI Solutions Architects to assist and support customers that are building solutions with our newest AI technology. At NVIDIA, our solutions architects work across different teams and enjoy helping customers with the latest Accelerated Data Analytics and Deep Learning software and hardware platforms. We're looking to grow our company, and build our teams with the smartest people in the world. Would you like to join us at the forefront of technological advancement?
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. This role is an excellent opportunity to work in an interdisciplinary team at NVIDIA! You will partner closely with ISVs, product, engineering, developer relations, business development, sales, and segment teams to identify high-impact use cases, develop early POCs and build repeatable enablement.
What You Will Be Doing:
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
What We Need To See:
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
Ways To Stand Out From The Crowd:
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.
Applications for this job will be accepted at least until June 28, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.