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

NVIDIA

Solutions Architect developing AI applications for grid modernization in the power and utilities sector. Collaborating with industry teams and partners to create innovative solutions.

Posted 7/20/2026full-timeCalifornia, Texas • 🇺🇸 United StatesMid-LevelSenior💰 $152,000 - $287,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in power-systems engineering and GPU-accelerated solutions, with a strong foundation in grid applications and modeling tools. Proficient in translating complex power-system challenges into innovative workflows using advanced technologies.

Highest-signal resume keywords

MS Or PhD In Electrical EngineeringPower-Systems EngineeringGrid Applications ExperiencePython Programming SkillsDeep Learning Frameworks (PyTorch, TensorFlow)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Power-System ModelingGPU-Accelerated WorkflowsLoad ForecastingRenewable Generation ForecastingSCADA/EMS/ADMS/DERMSContingency AnalysisMATLAB/SimulinkPSS®EGridLAB-DPandapower

Tools & Technologies

NVIDIA TechnologyAI StackOpenDSSMATPOWER/PYPOWERPowerWorldDIgSILENT PowerFactoryGPU Parallel Computing

Industry Keywords

Power And Utilities SectorGrid Data ModelsIEC StandardsNERC/FERC Regulatory EnvironmentISO/RTO Markets

Tech Stack

Tools & technologies

PythonPyTorchTensorflow

About the role

Key responsibilities & impact

Partner with our industry and account teams to understand customer goals, strategies, and technical needs
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
Help develop industry direction by integrating NVIDIA technology into AI, HPC, and enterprise GPU and networking architectures for grid applications
Collaborate primarily through virtual tools, with up to 20% travel required

Requirements

What you’ll need

MS or PhD in Electrical or Power Systems Engineering, Computer Science, Applied Mathematics, Physics, or related experience
Extensive practical understanding of the power and utilities sector and power-system basics
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
Ability to translate power-system problems into GPU-accelerated workflows using NVIDIA's accelerated-computing and AI stack
Familiarity with grid data models, standards, and protocols — CIM (IEC 61970/61968), IEC 61850, DNP3, and OPC UA
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
Solid Python skills and familiarity with GPU parallel computing
Experience with modern Deep Learning software architecture and frameworks (e.g., PyTorch, TensorFlow)

Benefits

Comp & perks

Competitive salaries
Generous benefits package