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Caterpillar

Makes heavy machinery, engines and gas turbines

Principal Software Engineer - Agentic AI and Simulation Automation

AI Application EngineeringPosted on Nov 6
Full-timeIrving, TX, USA

About the Job

Requirements

  • Advanced software engineering experience using Python and one or more of C++, C#, Java, Go, or Node.js.
  • Experience with APIs, distributed systems, containers, automated testing, continuous integration and continuous delivery (CI/CD), source control, and observability.
  • Experience with cloud platforms and cloud-native architectures, including Docker and Kubernetes.
  • Ability to lead architecture and technical delivery across multiple teams.
  • Strong communication, mentoring, problem-solving, and cross-functional collaboration skills.
  • Experience using AI-assisted development tools such as GitHub Copilot, Claude, or Cursor.
  • Experience designing and delivering production agentic AI, generative AI, or intelligent automation systems.
  • Experience with NVIDIA NIM, NeMo, Nemotron, or comparable foundation-model and inference ecosystems.
  • Experience with NVIDIA Cosmos or comparable world foundation models for Physical AI, scenario generation, and simulation augmentation.
  • Experience connecting AI agents to NVIDIA Omniverse, Isaac Sim, OpenUSD, or other engineering simulation platforms.
  • Strong Python, API, distributed systems, event-driven workflow, and backend services experience.
  • Experience with retrieval-augmented generation (RAG), embeddings, vector search, knowledge graphs, semantic data models, structured outputs, and multimodal models.
  • Experience with AI evaluation datasets, test harnesses, security controls, observability, and human-in-the-loop governance.
  • Experience deploying GPU inference using Docker, Kubernetes, NVIDIA GPUs, and CoreWeave or comparable GPU cloud infrastructure.

Responsibilities

  • Define the architecture for agentic simulation and multi-agent engineering workflows.
  • Build agents that interact with simulation engines, digital twins, APIs, datasets, and engineering tools.
  • Lead automated map-to-simulation, site-to-simulation, scenario-generation, and experiment-planning workflows.
  • Apply foundation models and multimodal AI to simulation configuration, monitoring, troubleshooting, analysis, and reporting.
  • Establish tool calling, workflow state, memory, human approvals, guardrails, observability, and auditability.
  • Create evaluation frameworks for accuracy, reliability, reproducibility, latency, cost, safety, and task completion.
  • Integrate AI services with NVIDIA Omniverse, Isaac Sim, OpenUSD, Cosmos, databases, knowledge systems, and cloud services.
  • Deploy and scale GPU inference and agent workloads on CoreWeave and Kubernetes.
  • Own a major technical capability across multiple teams and programs.
  • Translate ambiguous business and engineering problems into scalable architectures and production software.
  • Lead architecture reviews, technical investigations, design decisions, and engineering standards.
  • Balance research and prototyping with secure, maintainable, production-ready delivery.
  • Mentor senior and developing engineers and support technical hiring and onboarding.
  • Partner across simulation, robotics, autonomy, controls, AI, data, cloud, product, and customer-facing organizations.
  • Establish a clear reference architecture and technical roadmap for the capability area.
  • Deliver reusable platform components and measurable engineering outcomes within the first 12 months.
  • Improve quality, automation, scalability, and cross-team adoption while reducing duplicated solutions.
  • Develop technical depth across the broader engineering organization through mentoring and standards.

Desired Qualifications

  • Seven or more years of software development and three or more years developing machine learning, generative AI, or intelligent automation systems.
  • Experience delivering an AI-enabled capability from prototype through production.
  • Experience integrating agents with simulation, robotics, scientific computing, or enterprise engineering tools.
  • Working knowledge of Newton, physics simulation, and robotics workflows sufficient to orchestrate and evaluate tool use.
  • Preferred technology stack includes NVIDIA Cosmos, NIM, NeMo, Nemotron, Omniverse, Isaac Sim, OpenUSD, agentic AI, RAG, Python, CUDA, Docker, Kubernetes, and CoreWeave.

About the Company

Caterpillar

Makes heavy machinery, engines and gas turbines

Caterpillar makes construction and mining machines, diesel and natural gas engines, industrial gas turbines and locomotives for contractors, mines, energy companies and data center builders. It is the world's largest maker of construction and mining equipment, and its yellow Cat bulldozers and excavators work in nearly every country. Customers buy or rent machines through independent Cat dealers, while its engines and turbines generate electricity and push natural gas through pipelines. Caterpillar earns money from equipment sales and from the parts and repairs that dealers supply over a machine's working life. It was formed in 1925 when California's Holt and Best tractor companies merged, and it is based in Irving, Texas.

Company size
10,001+
Company stage
IPO
Headquarters
Irving, TX
Founded
1925

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