This role emphasizes that concluding step, converting NVIDIA's AI Factory, Omniverse, edge, and cybersecurity platforms into concrete results with our clients and collaborators. We are looking for an Energy OT / Industrial AI Solutions Architect to work with customers, partners, and NVIDIA engineers to bring AI into critical energy settings. This position links NVIDIA's AI platforms with workflows in control rooms, field operations, asset performance, and grid-edge that energy clients use. You will solve the last-mile deployment challenge to ensure secure and reliable AI across the energy value chain. This includes power generation, oil & gas and surface operations, transmission and distribution/grid, and renewables. You will apply NVIDIA technology and Python in operational-technology (OT) and industrial control system (ICS) environments. NVIDIA's accelerated-computing platforms have already made a strong impact with top energy operators, utilities, and OEMs!
We seek a curious, collaborative, and creative individual to advance work in industrial digital twins, edge AI, OT cybersecurity, generative and agentic AI, forecasting, and accelerated simulation. This role requires becoming a trusted technical advisor linking our industry teams, partners, and customers. Engaging with internal developers, researchers, data scientists, and senior leaders is vital and offers opportunities to work with diverse partners and challenges.
What you will be doing:- Partner with our industry and account teams to understand customer goals, strategies, and technical needs. Define and deliver high-value, GPU-accelerated AI solutions for energy operations that meet these needs.
- Develop industrial digital twins for plants, assets, and grids using Omniverse, OpenUSD, and PhysicsNeMo.
- Implement predictive asset maintenance and asset-performance management solutions.
- Deploy real-time AI at the edge for field, substation, and remote-site monitoring using Jetson/IGX and Metropolis.
- Improve OT/ICS cybersecurity and secure remote access with Morpheus and BlueField.
- Develop generative and agentic AI copilots for control-room and field workflows.
- Perform forecasting and rapid simulation for power systems, subsurface, and process engineering.
- Build industry direction by integrating NVIDIA technology into AI, HPC, and enterprise GPU and networking architectures for energy applications.
- 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, and be empowered to find the best way to make our partners and customers successful.
What we need to see:- MS or PhD in Electrical or Power Systems Engineering (or Chemical, Mechanical, or related engineering), Computer Science, Applied Mathematics, Physics, or equivalent experience.
- Strong practical understanding of one or more energy sectors and their operational technology. Experience includes OT/ICS and control systems like SCADA, EMS/ADMS/DERMS, DCS, and PI historians. Familiar with operational tasks such as asset-performance management and predictive maintenance.
- Experience with energy modeling and simulation tools - power-system tools such as pandapower, OpenDSS, GridLAB-D, MATPOWER/PYPOWER, PSS4, PSCAD, PowerWorld, DIgSILENT PowerFactory, or MATLAB/Simulink.
- Ability to transform energy and OT challenges into GPU-accelerated and AI workflows using NVIDIA's accelerated-computing and AI stack.
- Familiarity with grid and industrial data models, standards, and protocols.
- Familiarity with energy operations across the value chain - generation, grid operations and planning, interconnection, ISO/RTO markets, and field/surface operations - and the reliability and security regulatory environment.
- At least 4 years working in power systems, industrial/OT engineering, data science, or software development, or in comparable positions, demonstrating strong Python ability and understanding of GPU parallel processing.
- Experience with modern Deep Learning software architecture and frameworks and the Python data-science ecosystem.
- Comfortable with modern application-deployment practices such as Docker/Containers and Kubernetes, including deployment to the edge.
- Excellent communication skills - able to explain complex technical trade-offs to both engineers and executive partners. Strong problem structuring and self-direction help drive ambiguous projects involving multiple interested parties to results.
Ways to stand out from the crowd:- Applied data science and machine-learning R&D on power-systems, grid, or industrial-asset data.
- Creative generation of synthetic data to augment unusual energy and industrial datasets and stress-test models.
- Experience with network software development, including NVIDIA BlueField DPUs.
- Experience deploying AI in OT/ICS or industrial environments.
- Background with Agentic coding practices.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until July 21, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
