Principal Digital Architect, Simulation & Robotics Data

What you'll do

• Define data architecture for Physical AI and autonomous systems to enable learning and operation at scale.
• Establish data contracts, schemas, naming conventions, and metadata standards for information flow from machine systems.
• Design technical infrastructure including specific databases, programming languages, and testing approaches for applications.
• Create and maintain architectures for simulation, synthetic, and scenario-based data environments.
• Develop multimodal data architectures integrating sensor, video, image, telemetry, and robotics data sources.
• Establish governance, lineage, and traceability standards across training, validation, and testing datasets.
• Define metadata, labeling, versioning, and lifecycle management strategies for AI training datasets.
• Create scalable data patterns to support robotics training and world-model development.

What we're looking for

• Design data architecture for simulation, synthetic, and scenario-based data environments.
• Establish standards for data governance, lineage, traceability, metadata, and lifecycle management for AI training datasets.
• Design multimodal data architectures spanning sensor, video, image, telemetry, event, and robotics data sources.
• Develop technical infrastructure including specific databases, programming languages, and testing approaches.
• Perform requirements analysis to elicit and record business functionality and non-functional requirements.
• Demonstrate ability to define enterprise data domains, canonical models, and scalable architectures for AI ecosystems (preferred).
• Possess deep understanding of AI model development requirements including training data, fine-tuning, and synthetic data (preferred).
• Experience in physical AI, industrial data ecosystems, and edge-to-cloud architectures (preferred).
• Progressive career in software engineering and architecture with a focus on data, typically (preferred).