Simulation Platform Lead for Autonomous Systems

Caterpillar Brazil

Irving (TX)

On-site

USD 128,000 - 209,000

Full time

3 days ago

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Benefits offered by this job

Relocation assistance

Visa sponsorship

Onsite five days a week

Job summary

Caterpillar Inc. in Irving, TX is seeking a Simulation Platform Engineering Lead to guide the design, development and operation of a shared simulation platform for automation, digital twin, and robotics projects.

You will translate architecture roadmaps into practical software delivering scalable backend services across cloud, on-prem, and GPU-enabled environments. You will mentor engineers, run technical design reviews, implement APIs and tooling, and ensure reliability, performance, and

Qualifications

Strong software engineering experience building simulation platforms, developer platforms, distributed systems, backend services, or cloud-native applications.
Hands-on expertise in C++, Python, Go, Java, C#, or other relevant programming languages, with the ability to review and guide production-quality implementations.
Strong experience with Kubernetes, Docker, Linux, CI/CD pipelines, infrastructure automation, and software packaging and release practices.
Experience designing and implementing services across AWS, Azure, on-premises, or hybrid environments.
Knowledge of simulation architecture, runtime services, workload orchestration, asset and configuration management, and system integration.
Experience with NVIDIA Omniverse, Isaac Sim, Unreal Engine, Gazebo, AirSim, CARLA, or comparable simulation technologies is preferred.
Experience supporting GPU-based workloads, HPC environments, distributed execution, or large-scale engineering compute is preferred.
Knowledge of monitoring, logging, telemetry, observability, reliability, performance engineering, networking, and security practices.
Experience creating reusable APIs, SDKs, tools, libraries, and services for internal engineering teams.
Understanding of simulation verification and validation, automated regression testing, SIL, HIL, and continuous integration of simulation.

Responsibilities

Lead the design and implementation of core simulation platform and backend services supporting digital twin, robotics, autonomy, and verification workflows.
Translate platform architecture and technical roadmaps into executable designs, backlog priorities, engineering plans, and software deliverables.
Own technical delivery for simulation execution and lifecycle services, including job submission, configuration, scheduling, monitoring, results collection, and failure recovery.
Define and implement APIs, SDKs, service contracts, and integration patterns that allow simulation tools and engineering applications to use the platform consistently.
Design scalable platform solutions using Kubernetes, Docker, distributed systems, infrastructure automation, and cloud-native services across AWS, Azure, on-premises, and shared compute environments.
Build and improve continuous integration, automated testing, packaging, artifact management, deployment, and release workflows for simulation software.
Establish observability standards including logs, metrics, traces, dashboards, alerting, capacity visibility, and operational health for simulation services.
Support GPU-enabled and high-performance simulation workloads, including resource scheduling, workload isolation, performance tuning, and reliable execution at scale.
Lead integration of NVIDIA Omniverse, Isaac Sim, Unreal Engine, scenario systems, and other simulation frameworks with the broader platform ecosystem.
Create reusable developer tooling, command-line utilities, templates, and self-service workflows that improve onboarding and engineering productivity.
Partner with the Scenario Framework, Digital Twin, Robotics, Autonomy, Controls, QA, Product, and enterprise technology teams to ensure end-to-end system integration.
Lead technical design reviews, code reviews, troubleshooting, root-cause analysis, and resolution of complex platform and integration issues.
Improve platform reliability, scalability, security, maintainability, and performance through measurable engineering practices.
Mentor engineers, define implementation standards, and promote modularity, documentation, automated testing, and clear ownership.
Identify technical risks, dependencies, and delivery blockers and work with principal engineers and engineering leadership to resolve them.