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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Digital Architect - AI-Ready Data & Annotations - **Company:** Caterpillar - **Location:** Irving, TX, United States - **Salary:** $159,120.0 - $258,570.0 - **Contract:** Permanent contract - **Skills:** Training Data, Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Computing Platforms, Automation of Tests, Business Software, Databases, Continuous Integration, Data Architecture, Information Engineering, Data Infrastructure, Dataspaces, Digital Assets, Metadata, Operational Data Store, Software Engineering, Data Streaming, Digital Twin, Feature Engineering, Model Validation, Data Management, Data Objects, Data Pipelines, Programming Languages - **Published:** September 24, 2026 - **Apply:** https://dejobs.org/x/x/4C7FDFA0C5C54CB7AD01B0FEF89BFEC8/job/ ## About the Role * Data Architecture: Knowledge of processes, techniques and factors that affect data architecture; ability to design blueprints on how to integrate data resources for business processes and functional support. * Analytical Thinking: Knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems. * Platform Architecture: Knowledge of technologies and methods to design processing mechanisms and roadmaps to execute business application systems; ability to design these roadmaps and deploy supportive interfaces for end-users to access related systems, in accordance with standards and processes. * Requirements Analysis: Knowledge of tools, methods, and techniques of requirement analysis; ability to elicit, analyze and record required business functionality and non-functionality requirements to ensure the success of a system or software development project. * Target Architecture: Knowledge of target architecture; ability to develop the IT blueprint and roadmap while aligning the architecture and processes with business strategies and objectives roadmap while aligning the architecture and processes with business strategies and objectives Top Candidates Will Have: * Data Architecture & Domain Modeling -- Demonstrated ability to define enterprise data domains, canonical data models, data contracts, metadata strategies, and scalable architectures that support complex AI and autonomy ecosystems. * AI & Machine Learning Data Foundations -- Deep understanding of the data requirements for AI model development, including training data, fine-tuning datasets, feature engineering, vector data, model evaluation data, synthetic data, and data pipelines that support the AI lifecycle. * Data Platforms & Data Products -- Experience designing modern cloud and on-premise data platforms and data products architectures for massive data volumes and events, including streaming data, telemetry platforms, APIs, self-service data capabilities, and reusable data assets that accelerate engineering and data science teams. * Physical AI & Industrial Data Ecosystems -- Knowledge of machine telemetry, sensor data, digital twins, simulation data, edge-to-cloud architectures, and the unique challenges associated with autonomous systems and real-world operational data. * Strategic Architecture Leadership -- Ability to influence senior leaders, define architectural roadmaps, establish standards and patterns, govern technology decisions, and provide technical direction across multiple engineering organizations without direct authority. * Progressive career in software engineering and architecture with a focus on data (typically 12years+) * Strong understanding of Agile SDLC implementation in public cloud eco-system including environments management, test automation, peer review, CI/CD, resource optimization, etc. * Excellent communication skills and be able to deal with sensitive issues, mentor and coach and/or persuade others on new technologies, new applications, or potential solutions. ## Description The Principal Digital Architect for Physical AI Ready Data & Annotations is responsible for transforming enterprise data into reusable, governed, and consumable data products that accelerate simulation, training, and Physical AI. This role defines the operating model, architecture standards, and ownership framework for data products, ensuring they are discoverable, trusted, interoperable, and optimized for both human and machine consumption. The architect serves as the bridge between business domains, data engineering, and AI teams, enabling high-value data assets to be created once and consumed many times. Bottom line, you are creating the data foundation that enables AI innovation at scale. What You Will Do: * Developing detailed architecture deliverables to solve business problems. * Designing an application's technical infrastructure, such as specific databases, programming languages, utilities, and testing approaches. * Define the enterprise framework for Physical AI ready data products. * Establish standards for data product design, metadata, discoverability, quality, lineage, security, and lifecycle management. * Design reusable data objects and domain-oriented products that support Physical AI workloads. * Define data contracts and consumption interfaces to ensure consistent and reliable access across the organization. * Develop architecture standards for integrating labeling, annotation, curation, evaluation, and feedback processes into data products. * Drive consistency across domains while enabling decentralized ownership and domain accountability. ## Related Videos - [Harnessing the Power of Open Source's Newest Technologies](https://www.wearedevelopers.com/videos/1448-harnessing-the-power-of-open-source-s-newest-technologies) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Data: The Deciding Factor in AI Success](https://www.wearedevelopers.com/videos/100310-data-the-deciding-factor-in-ai-success) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)