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Maintains cross-program portfolio intelligence for autonomous construction initiatives. Synthesizes roadmaps, dependencies, milestones, capacity, risks, suppliers, partners, and customer learning into scenarios, trend analyses, executive reporting, and decision-ready recommendations. Supports roadmap governance, traceability, intake alignment, prioritization, and leadership reviews while preserving authoritative sources and accountability boundaries.

Develop and deploy AI-driven annotation, labeling, and captioning systems for robotics, computer vision, autonomy, and Vision-Language-Action datasets. Train and evaluate machine learning models, build scalable data pipelines, integrate human-in-the-loop workflows, and improve annotation quality. The role requires production software engineering, distributed systems, sensor-data expertise, and experience with computer vision or autonomous systems. Work is onsite in Irving, Texas, with relocation assistance and visa sponsorship available.

Develop and deploy AI-powered annotation, labeling, and captioning systems for robotics, computer vision, autonomy, and VLA datasets. Build data pipelines supporting human review, quality validation, and dataset publication; train and evaluate machine learning models; integrate Caterpillar systems with annotation providers; and ensure scalable, observable production services for heavy-equipment and construction environments.

Develop simulation logic, behavioral models, digital twins, and real-time 3D visualization experiences. Build high-fidelity scenes and environments with NVIDIA Omniverse, USD, and Omniverse Kit. Validate simulation models through data correlation, scenario testing, regression testing, and real-world telematics data. Contribute to integration pipelines, scripting utilities, automated testing frameworks, and modular C++ and Python libraries across digital-twin platforms and simulation engines.

Develop and deploy generative AI assistants, processing pipelines, tooling, and software using Python or Go. Build FastAPI services, edge-device components, CI/CD pipelines, and AWS infrastructure. Apply LLMs, prompt engineering, and modern agent architectures using LangChain and LangGraph. Collaborate with data scientists to productionize scalable analytics and AI solutions, and assist with Airflow-based machine learning pipelines. The role also requires software architecture, testing, technical writing, and cross-functional collaboration.

Leads development of high-fidelity digital twins, machine dynamics models, and reduced-order models for autonomous construction equipment. Establishes NVIDIA Newton simulation standards, validates models against real-world data, and enables robotics, autonomy, reinforcement learning, synthetic data, and virtual validation workflows. Collaborates across engineering, AI, controls, hydraulics, and machine systems teams while shaping Caterpillar’s long-term physical AI and simulation strategy.

As a Principal Software Engineer, you'll design and implement complex solutions in Dynamics 365, leading projects and ensuring high-quality applications while collaborating across teams.

Leads a Scrum team developing and modernizing Salesforce Sales Cloud and digital marketing capabilities. Designs scalable, secure solutions, integrates Salesforce with backend systems and portals, oversees deployment and quality standards, collaborates with architects and product owners, supports testing and debugging, and mentors junior developers. Requires extensive Salesforce architecture, configuration, coding, integration, deployment, Agile, and certification experience.

Leads enterprise-scale data architecture and solution design for Caterpillar’s digital ecosystem. Responsibilities include developing data architecture deliverables, designing system-to-system data flows and conceptual and logical data models, evaluating and deploying data solutions, and collaborating with engineering and product teams to address business requirements. Preferred experience includes cloud architecture using AWS or Azure, ETL, Snowflake, semantic modeling, and extensive data modeling.

Leads a scrum team developing AI-driven annotation automation for robotics, autonomy, computer vision, and VLA datasets. Designs and deploys automated labeling and captioning systems, trains and evaluates machine learning models, builds data pipelines incorporating human review and quality validation, integrates annotation providers, and improves service reliability and scalability. Provides hands-on technical leadership and mentorship while applying technologies such as NVIDIA Cosmos, computer vision, multimodal AI, and sensor-data workflows.