Simulation Infrastructure Engineer

Caterpillar Inc.•Irving, TX

1d•$112,710 - $183,140•Onsite

About The Position

Your Work Shapes the World at Caterpillar Inc. When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it. Help Build the Future of Caterpillar – Be Part of What's Next in Autonomous Construction Sites. At Caterpillar, technology always has a purpose, which is to solve our customers' toughest challenges. Construction autonomy is one of the most complex challenges in applied AI, and at Caterpillar, advancements in physical AI, simulation, sensing, and edge computing are turning things that once felt impossible—intelligent machines operating in dynamic jobsites—into reality. The Simulation Infrastructure Engineer will design, build, automate, and support the compute and platform environments used to develop and execute simulation, digital twin, robotics, and autonomy workloads. The role combines strong software engineering with cloud, container, GPU, and operational expertise. The engineer will create reliable, repeatable, and observable infrastructure that supports local development, shared environments, demonstrations, continuous integration, and large-scale simulation execution.

Requirements

Strong experience with AWS, Azure, Kubernetes, Docker, Linux, networking, CI/CD, and infrastructure automation.
Programming or scripting experience in Python, Go, C++, Bash, PowerShell, or comparable languages.
Experience building and operating distributed, cloud-native, or developer platform services.
Experience with Terraform, Helm, GitHub Actions, Azure DevOps, Jenkins, GitLab CI, Argo CD, or comparable automation tools.
Knowledge of observability, logs, metrics, traces, dashboards, alerting, reliability, and performance engineering.
Understanding of software packaging, artifact management, container registries, security scanning, release management, and environment governance.
Strong troubleshooting and root-cause analysis skills across application, container, operating system, network, storage, and infrastructure layers.
Ability to collaborate across platform, simulation, digital twin, QA, security, and enterprise infrastructure teams.
Bachelor's degree in Engineering, Computer Science, Information Technology, or a related discipline.
Typically 5+ years of software, cloud, infrastructure, platform, or simulation engineering experience.

Nice To Haves

Knowledge of GPU infrastructure, NVIDIA container tooling, GPU scheduling, HPC, Slurm, Ray, or distributed compute is strongly preferred.
Experience deploying or supporting NVIDIA Omniverse, Isaac Sim, Unreal Engine, robotics, AI, or simulation workloads is preferred.

Responsibilities

Design, implement, and support simulation infrastructure across AWS, Azure, on-premises, and hybrid environments.
Build reusable infrastructure and platform automation using Kubernetes, Docker, Terraform, Helm, scripting, and configuration management practices.
Create deployment patterns for simulation services, GPU workloads, NVIDIA Omniverse, Isaac Sim, Unreal Engine, and supporting tools.
Implement simulation workload scheduling, resource allocation, queueing, isolation, retries, and capacity management across CPU and GPU environments.
Support GPU and high-performance compute infrastructure, including drivers, container runtimes, resource visibility, scheduling, and performance troubleshooting.
Develop and maintain CI/CD pipelines for simulation builds, tests, containers, infrastructure, packaging, artifacts, and environment promotion.
Implement monitoring, logging, metrics, dashboards, alerting, auditability, and operational runbooks for simulation environments.
Improve platform reliability, availability, scalability, security, cost visibility, and recovery through automation and engineering standards.
Build self-service tooling and reusable environment templates for simulation developers and test teams.
Partner with runtime, scenario framework, rendering, digital twin, robotics, autonomy, and QA engineers to resolve deployment and integration issues.
Support simulation packaging, artifact repositories, dependency management, release workflows, and reproducible environment creation.
Participate in design reviews, code reviews, incident analysis, root-cause analysis, and continuous improvement activities.
Document infrastructure architecture, operational procedures, interfaces, dependencies, and support expectations.