Solutions Architect — Power and Utilities, AI Grid, Power Systems

NVIDIA • Us, TX

11d • Hybrid

About The Position

Join us at NVIDIA, where we are pushing the boundaries of what's possible in the power and utilities sector through innovative AI and accelerated computing solutions. As a Utilities and Energy Sector / Grid AI Solutions Architect, you will work with customers, partners, and fellow NVIDIA engineers to build AI applications and platforms that support grid modernization, simulation, interconnection acceleration, forecasting, resilience, and flexible load orchestration. You will bring to bear NVIDIA technology and Python across the energy and utility industries, impacting transmission and distribution system operators, generation owners, and grid-software vendors. Our team seeks a member to advance opportunities in grid simulation, forecasting, optimization, and applied AI. You will become a trusted technical advisor, connecting our industry teams, partners, and customers. Engaging with internal developers, researchers, data scientists, and senior leaders is a core part of the role, offering exposure to a wide range of partners and challenges!

Requirements

• MS or PhD in Electrical or Power Systems Engineering, Computer Science, Applied Mathematics, Physics, or related experience (or equivalent experience).
• Extensive practical understanding of the power and utilities sector and power-system basics, with direct experience in grid applications and tasks including SCADA/EMS/ADMS/DERMS, power-flow and state estimation, contingency and stability analysis, load and renewable forecasting, and grid asset management.
• Hands-on experience with power-system modeling and simulation tools such as pandapower, OpenDSS, GridLAB-D, MATPOWER/PYPOWER, PSS®E, PSCAD, PowerWorld, DIgSILENT PowerFactory, or MATLAB/Simulink, including real-time and hardware-in-the-loop platforms such as RTDS, OPAL-RT, or Typhoon HIL.
• Ability to translate power-system problems into GPU-accelerated workflows using NVIDIA's accelerated-computing and AI stack (CUDA, RAPIDS/cuGraph, cuOpt, Modulus, Omniverse, Earth-2, and Triton/TensorRT).
• Familiarity with grid data models, standards, and protocols — CIM (IEC 61970/61968), IEC 61850, DNP3, and OPC UA — along with utility data systems like OSIsoft/AVEVA PI historians and Esri ArcGIS Utility Network.
• Familiarity with grid operations and planning, interconnection, ISO/RTO markets, and the NERC/FERC regulatory environment.
• Over 4 years of professional experience in power-systems engineering, data science, or software development — or similar background — including solid Python skills and familiarity with GPU parallel computing.
• Experience with modern Deep Learning software architecture and frameworks (e.g., PyTorch, TensorFlow) and the Python data-science ecosystem (NumPy, pandas, RAPIDS).
• Comfortable with modern application-deployment practices such as Docker/Containers and Kubernetes.

Nice To Haves

• CUDA and GPGPU programming and optimization experience.
• Applied data science and machine-learning R&D on power-systems or grid data — load/price forecasting, renewable integration, outage prediction, anomaly detection, or graph neural networks on grid topology.
• Creative generation of synthetic data — synthetic load profiles, grid topologies, or fault scenarios — to augment unusual grid datasets and stress-test models.
• Experience with network software development.

Responsibilities

• Partner with our industry and account teams to understand customer goals, strategies, and technical needs, and to define and deliver high-value, GPU-accelerated grid solutions that meet them.
• Build and prototype solutions for specific grid problems such as interconnection-study and queue acceleration, load and renewable-generation forecasting, DER/DERMS orchestration, power-flow and contingency analysis at scale, predictive asset maintenance, wildfire and grid-resilience analytics, and data-center demand flexibility (e.g., EPRI DCFlex).
• Help develop industry direction by integrating NVIDIA technology into AI, HPC, and enterprise GPU and networking architectures for grid applications. These range from control-center and planning workloads in the datacenter to real-time analytics at the grid edge and substation.
• Strategically partner with flagship customers and industry-specific solution partners targeting our computing platform.
• Collaborate primarily through virtual tools, with up to 20% travel required.

Benefits

• competitive salaries
• generous benefits package
• equity

What This Job Offers

• Job Type: Full-time
• Career Level: Senior