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.

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.

Solutions Architect – OEM AI

Key skills