Jobs at Caterpillar

Defines enterprise architecture for streaming, batch, event-driven, analytics, and Physical AI data workloads. Designs ingestion, transformation, storage, governance, observability, security, resilience, and lifecycle-management patterns. Establishes platform guardrails, evaluates emerging technologies, and develops architectural roadmaps. Partners with engineering, cloud, and business teams to support AI and autonomy initiatives across large-scale industrial data ecosystems.

Defines data architecture for physical AI and autonomous systems, including data contracts, schemas, metadata, governance, lineage, and traceability. Designs multimodal architectures for sensor, video, image, telemetry, event, simulation, and robotics data. Establishes scalable data patterns for robotics training, synthetic data, world models, and AI development. Leads architectural roadmaps and standards while partnering with simulation, robotics, data engineering, and platform teams.

Build scalable automated testing for Java and Spring Boot microservices, REST APIs, event-driven services, databases, and distributed workflows. Develop comprehensive functional, integration, performance, resilience, and recovery tests; validate asynchronous behavior, state transitions, contracts, and failure modes. Integrate automation into CI/CD pipelines, establish quality metrics and release criteria, review AI-generated test code, and mentor engineering teams in test-first practices.

Design, build, test, and deploy secure, scalable backend microservices (Java/Spring Boot) on cloud platforms (AWS/Azure). Contribute to platform capabilities, CI/CD, observability, and AI-assisted development workflows; validate AI-generated code; collaborate in Agile teams; support Python or front-end tasks as needed; produce documentation and operational runbooks.

Defines enterprise architecture and operating standards for AI-ready data products supporting Physical AI, simulation, and machine learning. Establishes data domains, contracts, metadata, quality, lineage, security, lifecycle management, and reusable data objects. Integrates labeling, annotation, curation, evaluation, and feedback processes while aligning business, data engineering, and AI teams. Provides strategic architectural leadership across engineering organizations and develops scalable cloud, on-premise, telemetry, streaming, and edge-to-cloud data platform strategies.

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.

Manages pre-launch Physical AI and autonomy initiatives from intake through launch approval. Aligns Product, Commercial, Engineering, and Technical Program Management stakeholders on scope, timing, value, capacity, dependencies, risks, and resources. Builds launch decision packages, facilitates governance reviews, establishes milestones and objectives, and transitions approved programs into execution. Governs launched programs at the portfolio level while maintaining prioritization, sequencing, reporting, and continuous improvement across the initiative pipeline.

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.

Develops production-quality C++ localization software for autonomous and semiautonomous systems. Designs positioning and state-estimation algorithms using perception, inertial, and GNSS inputs; prototypes and validates solutions; supports architecture, requirements, functional safety, documentation, debugging, and product quality. Collaborates with and mentors localization team members. The role is onsite in Irving, Texas, with up to 10% domestic travel and visa sponsorship available for eligible applicants.

Designs, develops, and integrates simulation and digital twin capabilities for autonomous construction robotics. Builds high-fidelity 3D scenes, sensor simulations, and Omniverse-based pipelines using C++ and Python. Integrates simulation models with data systems, optimizes large-scale workflows, develops validation frameworks, and connects simulations to real-time visualization and operator experiences. The role also evaluates emerging tools, reduces the real-to-sim gap using machine data, and leads technical planning and mentoring.

Leads DevOps architecture for Caterpillar’s embedded and distributed autonomy platforms. Designs CI/CD pipelines, infrastructure-as-code frameworks, observability standards, automation tooling, and secure cloud-to-edge integrations. Governs reusable pipelines and dependency management, improves build and deployment performance, establishes automated testing and reliability practices, and mentors engineering teams. The role requires onsite work in Irving, Texas, with up to 10% international travel.

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.

Designs enterprise agentic AI architectures, including orchestration layers, tool integrations, retrieval patterns, testing, and infrastructure. Leads evaluation and deployment of emerging AI technologies, translates business requirements into scalable solutions, and advises cross-functional teams on architecture decisions. The role emphasizes multi-agent systems, LLMs, RAG, cloud AI platforms, MLOps, LLMOps, enterprise integration, and production AI systems.

Design, develop, validate, and deploy production-quality localization software for autonomous and semiautonomous systems. Research positioning algorithms, implement filtering solutions using perception, inertial, and GNSS inputs, contribute to architecture and functional safety, troubleshoot software, and mentor localization engineers. The role focuses on C++ development, robotics frameworks, navigation, real-time systems, sensor fusion, coordinate transformations, and vehicle dynamics.

Lead the design and development of scalable data pipelines, microservices, cloud-native ingestion systems, and streaming solutions. Collaborate with architects, engineers, product teams, and business stakeholders to build reliable data platforms using Python, Java, AWS services, SQL, and relational and NoSQL databases. Establish data quality, testing, monitoring, automation, and validation frameworks while optimizing performance and resolving production issues across distributed systems.

Develop Python data pipelines and business data objects for applications. Build and deploy CI/CD pipelines, implement source-to-target mappings, resolve complex technical issues, and perform unit and integration testing. The role also involves software design, architecture, quality practices, cross-functional collaboration, and continuous improvement. The position is onsite five days per week in Chicago or Peoria, Illinois, with no relocation assistance or visa sponsorship.

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.

Lead full-stack development for Caterpillar Financial’s Artemis platform using React, TypeScript, Python or Node.js, AWS, and generative AI. Design scalable features, enterprise integrations, reusable engineering patterns, automated tests, and CI/CD practices. Support production deployments, troubleshoot complex issues, guide architecture and security decisions, mentor developers, review code, and translate stakeholder feedback into technical solutions. The role requires building reliable, secure, and compliant AI-enabled workflows in a regulated financial-services environment.

Owns the product vision, feature decisions, and prioritized backlog for data engineering products while supporting project planning and execution. Partners with Scrum and technical product teams to communicate priorities, manage sprint objectives, oversee schedules and budgets, coordinate project stages, lead change decisions, and ensure successful delivery. The role requires strong product ownership, project management, agile collaboration, and knowledge of data ingestion, connectivity, ontology, annotation, quality, lifecycle, storage, and digital traceability.

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.