About the job
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Want to be part of the team that empowers NVIDIA's OEM technical counterparts to develop accelerated compute and AI solutions for their customers? We are looking for a hardworking and self-starting Solutions Architect with a passion for accelerated compute, data workflows and AI security to join our Solutions Architecture and Engineering team. This role focuses on scaling the efficiency of our information and protection integrations, ensuring our customers and partners are equipped to build the future of innovative defense.
Responsibilities
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.
Qualifications
Minimum
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.
Preferred
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.