Principal Architect – Digital Twin

Caterpillar•Irving, TX

14h•$147,760 - $240,110•Onsite

About The Position

The Principal Architect – Digital Twin is responsible for the architecture of the digital twins used to develop and validate Physical AI, simulation, and autonomy. The role defines machine, jobsite/environment, and sensor twins that are simulation-ready, physically based, versioned, and validated against real machines and sites. Machine twins cover kinematics, multibody dynamics, hydraulics, powertrains, implements, tools, and material interaction. Jobsite twins encompass terrain, design surfaces, geospatial data, infrastructure, changing site conditions, weather, and lighting. Sensor twins model cameras, LiDAR, radar, GNSS, and IMUs in their true machine-mounted frames. The architect defines pipelines that convert CAD, PLM, survey, and reality-capture data into simulation-ready OpenUSD assets and environments for NVIDIA Omniverse / Isaac Sim and Unreal Engine. The role also establishes data models connecting twins to machine telemetry and fleet data; validation and correlation programs that quantify twin fidelity; and synthetic-data and neural-reconstruction workflows, including 3D Gaussian Splatting, NeRF, and real-to-sim. The position works closely with the Simulation Engine architect and AI Factory architect. The role bridges architecture and engineering by translating the digital twin vision into detailed solution designs, reusable patterns, standards, and implementation guidance, and by guiding engineering teams. It develops architecture deliverables, designs application technical infrastructure, leads evaluation and deployment of technologies, and collaborates across functions to deliver digital solutions aligned with business requirements. The position is full-time and requires working onsite five days a week at the Irving, Texas office. Domestic relocation assistance and visa sponsorship are available.

Requirements

Knowledge of requirements-analysis tools, methods, and techniques, and ability to elicit, analyze, and document business functionality and non-functional requirements.
Analytical thinking skills, including ability to identify root causes and develop alternative solutions.
Knowledge of platform architecture and ability to design processing mechanisms, roadmaps, and supportive interfaces in accordance with standards and processes.
Knowledge of target architecture and ability to develop IT blueprints and roadmaps aligned with business strategy and objectives.
Effective communication skills to transmit, receive, and accurately interpret ideas, information, and needs.
Bachelor’s degree in Computer Science, Robotics, Mechanical Engineering, Physics, or a related field.
Ability to work full-time onsite at the Irving, TX office five days a week.

Nice To Haves

Master’s or doctoral degree.
Experience delivering physically based digital twins of machines, vehicles, robots, or industrial sites for simulation, validation, or AI training, including fidelity tiers, versioning, and lifecycle.
Hands-on NVIDIA Omniverse (Kit, Isaac Sim, Replicator, Nucleus) and OpenUSD experience, including composition, schemas, USD Physics, SimReady assets, and scaled CAD-to-USD conversion; Unreal Engine or Unity experience for large outdoor environments.
Experience with multibody dynamics, articulations, hydraulics, powertrains, and implement-material interaction using URDF, MJCF, or USD Physics; model calibration and system identification against measured data; CAE / PLM exposure such as Siemens NX, Ansys, Modelica, or Adams.
Experience building 3D environments from drone photogrammetry, LiDAR, survey and design surfaces, and GIS data; procedural site generation; construction or mining site data experience such as Trimble, Topcon, Hexagon, or Cat MineStar / Grade.
Experience with physically based camera, LiDAR, radar, GNSS, and IMU models, including calibration frames and environmental effects; synthetic data with ground truth and domain randomization using Omniverse Replicator.
Experience with 3D Gaussian Splatting, NeRF, or world foundation models such as NVIDIA Cosmos to create sensor-realistic environments from fleet data in combination with physics-based twins.
Experience with data models and pipelines linking twins to live machine telemetry and fleet data using ROS 2, MQTT, Kafka, DDS, or edge-to-cloud architectures.
Experience establishing twin-fidelity acceptance criteria, test-data correlation, scenario-based and regression testing, HIL / SIL correlation, and quantified sim-to-real gap metrics.
Strong Python and C++ skills; GPU / CUDA workloads, containers and Kubernetes, CI/CD, cloud (AWS / Azure), and comfort with AI coding tools.
Architecture leadership translating architecture into implementation plans, reusable patterns, and standards across teams, and technical leadership of engineers.
Domain exposure to off-highway, construction, mining, or agriculture machines, or digital twin programs at NVIDIA, Applied Intuition, Volvo Autonomous Solutions, Komatsu, John Deere, Siemens, or Duality AI.

Responsibilities

Develop detailed architecture deliverables to solve business problems.
Design application technical infrastructure, including databases, programming languages, utilities, and testing approaches.
Lead evaluation and deployment of technologies that add to or enhance digital technical capabilities.
Address business requirements for applications and collaborate with cross-functional teams to deliver digital solutions and business results.
Define architectures for machine, jobsite/environment, and sensor digital twins used in Physical AI, simulation, and autonomy development and validation.
Define asset and scene pipelines that convert CAD, PLM, survey, and reality-capture data into simulation-ready OpenUSD assets and environments.
Define data models connecting twins to machine telemetry and fleet data so twins reflect as-operated machines and as-built sites.
Establish validation and correlation programs, including test-data correlation, scenario-based testing, regression testing, and telematics comparison, to quantify twin fidelity.
Develop synthetic-data and neural-reconstruction workflows to scale twin creation.
Translate the digital twin vision into detailed solution designs, reusable patterns, standards, and implementation guidance, and guide engineering teams.
Work closely with the Simulation Engine architect and AI Factory architect.