Caterpillar
Principal Software Engineer - Simulation Data, Validation & Infrastructure
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Leads architecture and implementation of enterprise-scale simulation data, validation, GPU infrastructure, and reproducible pipelines. Designs data ingestion, digital-twin models, verification frameworks, synthetic-data systems, Kubernetes-based GPU workloads, observability, security, CI/CD, and infrastructure-as-code. Provides principal-level technical leadership across teams, drives architecture standards, mentors engineers, and partners across simulation, robotics, autonomy, AI, cloud, and data organizations.
Career Area:
Technology, Digital and Data
Job Description:
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.
Summary
At Caterpillar, technology has a purpose: to solve our customers' toughest challenges. Construction autonomy and Physical AI require trusted digital twins, high-fidelity simulation, scalable GPU computing, intelligent automation, and rigorous validation. This Principal Engineer role is a hands-on technical leadership position responsible for architecture, critical implementation, engineering standards, cross-team alignment, and mentoring.
Role Purpose
Lead the data, validation, and accelerated-computing foundation required to operate simulation at enterprise scale, connecting physical-machine evidence with virtual-machine behavior through reproducible pipelines and trusted infrastructure.
What You Will Do
• Architect machine-data and simulation-data ingestion, processing, curation, storage, and serving pipelines.
• Define data models connecting machines, digital twins, environments, scenarios, datasets, models, and results.
• Establish verification and validation frameworks, correlation methods, automated regression tests, and quality gates.
• Build synthetic-data generation, automatic annotation, dataset lineage, versioning, and reproducibility capabilities.
• Architect scalable NVIDIA GPU execution across CoreWeave, on-premises clusters, cloud, and HPC environments.
• Operate batch simulation, distributed training, inference, rendering, and synthetic-data workloads using Kubernetes.
• Define observability, security, workload scheduling, cost controls, resource quotas, and failure-recovery practices.
• Establish infrastructure as code and CI/CD for simulation services, models, datasets, and GPU workloads.
Principal-Level Leadership Expectations
• 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.
Required Skills and Experience
• 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, CI/CD, source control, and observability. Principal Engineer Job Description Page 3
• Experience with cloud platforms and cloud-native architectures, including Docker and Kubernetes.
• Demonstrated 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.
• Deep experience with CoreWeave or comparable GPU cloud platforms, Kubernetes, Docker, NVIDIA Container Toolkit, GPU operators, scheduling, and workload optimization.
• Experience supporting NVIDIA Omniverse, Isaac Sim, Isaac Lab, Newton, Cosmos, Replicator, training, inference, and synthetic-data workloads.
• Experience with CUDA-aware systems, multi-GPU execution, distributed workloads, job queues, autoscaling, and GPU utilization monitoring.
• Experience with telemetry, time-series, sensor, image, video, LiDAR, segmentation, depth, map, and simulation ground-truth data.
• Experience with SQL, NoSQL, object storage, time-series databases, Kafka, Spark, Flink, or comparable technologies.
• Experience with Terraform, Helm, GitOps, CI/CD, secrets management, security controls, and reproducible environments.
• Experience with OpenTelemetry, Prometheus, Grafana, logging, tracing, cost monitoring, and service-level objectives.
• Knowledge of statistical validation, uncertainty, tolerance analysis, model correlation, and traceable acceptance criteria.
Top Candidate / Preferred Experience
• Seven or more years of software, data, platform, cloud, HPC, or infrastructure engineering experience.
• Five or more years building production data pipelines or accelerated-computing platforms.
• Experience processing large-scale machine telemetry, sensor, simulation, or Physical AI datasets.
• Experience designing secure, reproducible GPU platforms for multiple engineering teams.
Preferred Technology Stack
CoreWeave | Kubernetes | NVIDIA GPUs | CUDA | Docker | Terraform | Helm | Omniverse | Isaac Sim | Newton | Replicator | Cosmos | Prometheus | Grafana
Success Measures
• 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.
ADDITIONAL DETAILS
Summary Pay Range:
$147,760.00 - $240,110.00
Compensation and benefits offered may vary depending on multiple individualized factors, job level, market location, job-related knowledge, skills, individual performance and experience. Please note that salary is only one component of total compensation at Caterpillar.
Benefits:
Subject to plan eligibility, terms, and guidelines. This is a summary list of benefits.
* These benefits also apply to part-time employees
Posting Dates:
Any offer of employment is conditioned upon the successful completion of a drug screen.
Caterpillar is an Equal Opportunity Employer, Including Veterans and Individuals with Disabilities. Qualified applicants of any age are encouraged to apply.
Not ready to apply? Join our Talent Community.
Technology, Digital and Data
Job Description:
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.
Summary
At Caterpillar, technology has a purpose: to solve our customers' toughest challenges. Construction autonomy and Physical AI require trusted digital twins, high-fidelity simulation, scalable GPU computing, intelligent automation, and rigorous validation. This Principal Engineer role is a hands-on technical leadership position responsible for architecture, critical implementation, engineering standards, cross-team alignment, and mentoring.
Role Purpose
Lead the data, validation, and accelerated-computing foundation required to operate simulation at enterprise scale, connecting physical-machine evidence with virtual-machine behavior through reproducible pipelines and trusted infrastructure.
What You Will Do
• Architect machine-data and simulation-data ingestion, processing, curation, storage, and serving pipelines.
• Define data models connecting machines, digital twins, environments, scenarios, datasets, models, and results.
• Establish verification and validation frameworks, correlation methods, automated regression tests, and quality gates.
• Build synthetic-data generation, automatic annotation, dataset lineage, versioning, and reproducibility capabilities.
• Architect scalable NVIDIA GPU execution across CoreWeave, on-premises clusters, cloud, and HPC environments.
• Operate batch simulation, distributed training, inference, rendering, and synthetic-data workloads using Kubernetes.
• Define observability, security, workload scheduling, cost controls, resource quotas, and failure-recovery practices.
• Establish infrastructure as code and CI/CD for simulation services, models, datasets, and GPU workloads.
Principal-Level Leadership Expectations
• 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.
Required Skills and Experience
• 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, CI/CD, source control, and observability. Principal Engineer Job Description Page 3
• Experience with cloud platforms and cloud-native architectures, including Docker and Kubernetes.
• Demonstrated 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.
• Deep experience with CoreWeave or comparable GPU cloud platforms, Kubernetes, Docker, NVIDIA Container Toolkit, GPU operators, scheduling, and workload optimization.
• Experience supporting NVIDIA Omniverse, Isaac Sim, Isaac Lab, Newton, Cosmos, Replicator, training, inference, and synthetic-data workloads.
• Experience with CUDA-aware systems, multi-GPU execution, distributed workloads, job queues, autoscaling, and GPU utilization monitoring.
• Experience with telemetry, time-series, sensor, image, video, LiDAR, segmentation, depth, map, and simulation ground-truth data.
• Experience with SQL, NoSQL, object storage, time-series databases, Kafka, Spark, Flink, or comparable technologies.
• Experience with Terraform, Helm, GitOps, CI/CD, secrets management, security controls, and reproducible environments.
• Experience with OpenTelemetry, Prometheus, Grafana, logging, tracing, cost monitoring, and service-level objectives.
• Knowledge of statistical validation, uncertainty, tolerance analysis, model correlation, and traceable acceptance criteria.
Top Candidate / Preferred Experience
• Seven or more years of software, data, platform, cloud, HPC, or infrastructure engineering experience.
• Five or more years building production data pipelines or accelerated-computing platforms.
• Experience processing large-scale machine telemetry, sensor, simulation, or Physical AI datasets.
• Experience designing secure, reproducible GPU platforms for multiple engineering teams.
Preferred Technology Stack
CoreWeave | Kubernetes | NVIDIA GPUs | CUDA | Docker | Terraform | Helm | Omniverse | Isaac Sim | Newton | Replicator | Cosmos | Prometheus | Grafana
Success Measures
• 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.
ADDITIONAL DETAILS
- This position requires the candidate to be based in Irving, TX (Dallas)
- Domestic relocation assistance is available for this position.
- Visa sponsorship is available for this position
Summary Pay Range:
$147,760.00 - $240,110.00
Compensation and benefits offered may vary depending on multiple individualized factors, job level, market location, job-related knowledge, skills, individual performance and experience. Please note that salary is only one component of total compensation at Caterpillar.
Benefits:
Subject to plan eligibility, terms, and guidelines. This is a summary list of benefits.
- Medical, dental, and vision benefits*
- Paid time off plan (Vacation, Holidays, Volunteer, etc.)*
- 401(k) savings plans*
- Health Savings Account (HSA)*
- Flexible Spending Accounts (FSAs)*
- Health Lifestyle Programs*
- Employee Assistance Program*
- Voluntary Benefits and Employee Discounts*
- Career Development*
- Incentive bonus*
- Disability benefits
- Life Insurance
- Parental leave
- Adoption benefits
- Tuition Reimbursement
* These benefits also apply to part-time employees
Posting Dates:
Any offer of employment is conditioned upon the successful completion of a drug screen.
Caterpillar is an Equal Opportunity Employer, Including Veterans and Individuals with Disabilities. Qualified applicants of any age are encouraged to apply.
Not ready to apply? Join our Talent Community.
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