Solutions Architect – OEM AI

NVIDIA

. Design and implement GPU-accelerated pipelines capable of processing very large (multi-TB and PB sizes) cyber, network, and industry datasets .

Posted 11/10/2026full-timeRemote • California • United StatesMid-LevelSenior💰 $152,000 - $287,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in GPU-accelerated pipelines, AI workloads, and cybersecurity solutions, with a strong foundation in machine learning and data science. Proven ability to lead technical initiatives and communicate complex concepts effectively to diverse audiences.

Highest-signal resume keywords

GPU-Accelerated Pipeline DevelopmentMachine Learning ExpertisePython, C/C++, Bash Coding SkillsTechnical Leadership ExperienceNVIDIA Tools Integration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningStatisticsPipeline DevelopmentBig Data FrameworksAI FrameworksData ScienceCybersecurityAgentic AIGraph Neural Networks

Soft Skills

Exceptional Communication SkillsAnalytical Problem-SolvingMultitasking AbilityPresentation Skills

Tools & Technologies

NVIDIA MorpheusNVIDIA RAPIDSNVIDIA DPU DOCASplunkSparkLinux UtilitiesDistributed Computing Environments

Industry Keywords

CybersecurityAI Compute WorkloadsThreat DetectionData Pipeline ArchitecturesPublic Speaking

Tech Stack

Tools & technologies

Cyber SecurityLinuxOpen SourcePythonSparkSplunkC++

About the role

Key responsibilities & impact

Design and implement GPU-accelerated pipelines capable of processing very large (multi-TB and PB sizes) cyber, network, and industry datasets
Develop proof-of-concept discussions that assist and illustrate how to address accelerated and AI compute workloads to tackle real customer issues
Function as a technical lead and liaison between NVIDIA engineering, product teams, and OEM partners to drive innovative technical and business strategies
Guide the development of Agentic AI workflows, including semantic search, retrieval-augmented generation (RAG), and Graph Neural Network (GNN) based applications for threat detection
Translate complex AI and cybersecurity research into actionable, deployable architectures for enterprise and government customers
Integrate NVIDIA software and tools with OEM partners’ offerings
Drive adoption, build proof-of-concept technologies, and align technical messaging with OEMs’ broader product strategies

Requirements

What you’ll need

BS, MS, or PhD in Computer Science, AI Engineering, Data Science, or a related field (or equivalent experience)
5+ years of experience in roles focused on technology, including Solutions Architecture, Data Science, or AI Research
Deep expertise in supervised and unsupervised machine learning, deep learning, and statistics, specifically applied to loosely-structured data and security logs
Strong coding, debugging, and pipeline development skills using Python, C/C++, Bash, and Linux utilities
Hands-on experience with big data and AI frameworks, including GPU acceleration, Spark, and distributed computing environments
Exceptional communication and presentation skills, with an ability to distill complex technical topics into clear, understandable content for an engaged audience
Strong analytical and problem-solving skills, along with an ability to multitask efficiently in a dynamic environment
Direct experience building, deploying, or contributing to NVIDIA opensource projects and tools like Morpheus, RAPIDS, NVIDIA DPU DOCA or similar NVIDIA accelerated compute libraries
Demonstrated expertise integrating AI workloads with Splunk or data pipeline architectures or AI security protection ecosystems
Experience working in a technical leadership role or principal investigator capacity on large-scale or secure enterprise projects
Background in Agentic AI, LLM deployment, and building ingestion/retrieval technologies
Public speaking experience at industry conferences or large technical events

Benefits

Comp & perks

Highly competitive salaries
Comprehensive benefits package
Equity