Senior AI Solutions Architect - Industrial Engineering

NVIDIA is a leader in computer graphics and AI technology, seeking a Senior Solutions Architect to support Industrial Engineering accounts. This role involves collaborating with engineering software developers and customer teams to enhance simulation performance and implement NVIDIA's advanced computing solutions.

Responsibilities:

• Support Business Development and Sales teams as part of a small Solutions Architecture team, partnering with Industry Business leads, Account Managers, and Developer Relations managers to drive ecosystem success across Industrial Engineering accounts (CAE/CFD/FEA ISVs, simulation platforms, and industrial OEMs)
• Work directly with engineering-software developers and customer simulation teams in a customer-facing setting
• Help developers GPU-accelerate and scale CAE/CFD/FEA solvers and structural, thermal, and fluid-dynamics workloads on NVIDIA accelerated computing and HPC platforms
• Apply physics-informed ML and surrogate modeling (e.g., NVIDIA PhysicsNeMo / Modulus) and NVIDIA Omniverse digital twins to compress design, simulation, and optimization cycles
• Analyze simulation and engineering application architectures and find opportunities for acceleration
• Provide feedback and collaborate with engineering, product, and research teams
• Deliver trainings, hackathons, and technical demonstrations on NVIDIA solutions and platforms

Requirements:

• MS/PhD in Mechanical, Aerospace, Civil, or Chemical Engineering, Computational Science, Applied Mathematics, Physics, or a related technical field (or equivalent experience)
• 4+ years working in CAE/CFD/FEA or computational engineering — numerical simulation, solver development, or HPC-based engineering analysis
• Hands-on experience with commercial or open-source simulation tools (e.g., Ansys, Siemens Simcenter, Altair, COMSOL, Cadence Fidelity CFD, OpenFOAM, LS-DYNA, Abaqus)
• Strong grounding in numerical methods (FEM/FVM/spectral), linear algebra, and the mathematics behind physics solvers
• Experience in algorithm programming using languages like Python and C/C++, with familiarity GPU-accelerating compute-intensive workloads
• Familiarity with accelerated computing platforms, GPU-based distributed systems, and HPC clusters/schedulers (e.g., Slurm)
• Familiarity with containers, numerical libraries, modular software design, version control, GitHub
• Experience designing, prototyping, and building complex solutions for customers; able to reason across components such as data pipelines, solvers, compute, networking, and orchestration
• Solid written and oral communication skills and familiarity with collaborative environments
• Team player who can learn, react, and adapt quickly, with an attitude to work in a fast-paced environment
• Experience GPU-accelerating CFD/FEA solvers, or developing physics-ML and surrogate models (NVIDIA PhysicsNeMo/Modulus, physics-informed neural networks)
• Experience with NVIDIA Omniverse, OpenUSD, and digital-twin workflows for industrial and engineering simulation
• Development experience with NVIDIA software libraries and GPUs, including CUDA and CUDA-X math libraries (cuBLAS, cuSPARSE, cuDNN)
• Experience with Kubernetes, distributed training, and large-scale inference
• Experience supporting or using PCIe accelerators such as GPUs, FPGAs, DSPs from evaluation to production stages