Principal Data Architect, Simulation & Robotics Data

What you'll do

• Define the data architecture for Physical AI and autonomous systems to enable learning and reasoning at scale.
• Establish data contracts, standards, schemas, and naming conventions for reliable information flow from machine systems.
• Design multimodal data architectures for sensor, video, image, telemetry, event, and robotics data sources.
• Define and maintain architectures for simulation, synthetic, and scenario-based data environments.
• Establish data governance, lineage, and traceability across training, validation, and testing datasets.
• Create scalable data patterns for robotics training, world-model development, and Physical AI initiatives.
• Define metadata, labeling, versioning, and lifecycle management strategies for AI training datasets.
• Develop detailed architecture deliverables and roadmaps to solve complex business problems.

What we're looking for

• Develop detailed architecture deliverables to solve business problems and design technical infrastructure including databases and programming languages.
• Define and maintain architecture for simulation, synthetic, and scenario-based data environments.
• Establish data standards, governance, lineage, and traceability across training, validation, and testing datasets.
• Design multimodal data architectures spanning sensor, video, image, telemetry, event, and robotics data sources.
• Define metadata, labeling, versioning, and lifecycle management strategies for AI training datasets.
• Demonstrate ability to define enterprise data domains, canonical data models, and scalable architectures for AI and autonomy ecosystems (preferred).
• Possess deep understanding of data requirements for AI model development, including training data, feature engineering, and synthetic data (preferred).
• Maintain a progressive career in software engineering and architecture with a focus on data, typically (preferred).