Intel
Physical AI Solutions Architect
$256K–$361K
US, Oregon, Hillsboro +3 · Full-time · Posted Sep 4, 2026
- Location
- US, Oregon, Hillsboro
US, California, Folsom
US, California, Santa Clara
US, Arizona, Phoenix - Experience
- 12 or more years with a Bachelor's degree, 8 or more years with a Master's degree, or 6 or more years with a PhD.
- Education
- Bachelor's degree in Computer Science, Engineering, Robotics, AI, or related field.
About the job
Architects and deploys end-to-end Physical AI and robotics solutions for enterprise customers using Intel technologies, while informing Intel’s product roadmap and go-to-market strategy.
What you'll do
- Advise partners and enterprise customers on robotics solution architecture, deployment, and integration with IT, OT, edge, and cloud infrastructure.
- Guide robotics development from data collection and simulation through model optimization, hardware deployment, and fleet-scale operations; lead proofs of concept and validation.
- Represent customer and market needs to Intel teams and influence product roadmaps, investments, and adoption.
What they ask for
- Bachelor’s degree in Computer Science, Engineering, Robotics, AI, or a related field.
- 12+ years of experience with a Bachelor’s, 8+ years with a Master’s, or 6+ years with a PhD.
- Demonstrated experience deploying end-to-end robotics or Physical AI solutions in enterprise environments, from development through production.
- Expertise in AI systems architecture, deep learning models, algorithm optimization for CPUs and GPUs, and integrating AI and robotics workloads into enterprise infrastructure.
Nice to have
- Experience with humanoid, industrial, warehouse, mobile, or service robotics.
- Familiarity with ROS/ROS2, Isaac Sim, Gazebo, MuJoCo, Webots, or other robotics simulation platforms.
Pay
$255,850.00-361,200.00 USD (total compensation)
Tools
CPUs, GPUs, ROS/ROS2, Isaac Sim, Gazebo, MuJoCo, Webots
AI focus
Applies AI to robotics across data collection, simulation, model training and optimization, deployment on robotic hardware, and fleet operations; includes AI systems architecture and deep learning.
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