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# Omniverse Platform Engineer / Technical Lead

- **Company:** zuven Technologies
- **Location:** Chillicothe, IL, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Automation of Tests, Microsoft Azure, C++ (Programming Language), CMake, Code Generation, Nvidia CUDA, System Configuration, Software Debugging, Programming Tools, Distributed Systems, Middleware, Hardware Interface Design, Python (Programming Language), Real Time Simulation, Software Engineering, Systems Integration, Large Language Models, Generative AI, Isaac Sim, Containerization, Kubernetes, Build Tools, Slurm, Hardware Infrastructure, Unreal Engine, NVIDIA Omniverse, Lidar, Docker, Web Api
- **Published:** October 30, 2026
- **Apply:** https://www.careerjet.com/jobad/us2b7640e0b4d37c7ef094b9a136508beb

## About the Role

We are seeking an execution-focused Technical Lead & Omniverse Platform Engineer to anchor a dedicated 6-person delivery squad building a common, scalable Simulation Foundation Platform. In this role, you will be based onsite in Dallas, TX, serving as the technical anchor for five remote junior-to-mid-level engineers across specialized tracks: Infrastructure, Scenario Orchestration, Sensor & Rendering, QA Automation, and Core Platform Services. You will own the technical direction of the platform, break down the evolving roadmap into concrete sprint deliverables, eliminate blockers, and directly contribute hands-on code using NVIDIA Omniverse, OpenUSD, and Isaac Sim. As an AI-first engineering team, you will champion the integration of AI-assisted coding tools, agentic development workflows, and automated generation pipelines across the entire squad to drive sprint velocity. Required Skills - NVIDIA Omniverse OpenUSD Python C++ Isaac Sim Job Requirements - Technical Leadership &
Delivery: 5+ years of hands-on software development experience with at least 1 2 years serving in a technical lead, team lead, or sprint coordination capacity, guiding developers and translating project roadmaps into actionable sprint deliverables. NVIDIA Omniverse Ecosystem: Proven hands-on production experience architecting and implementing solutions within the NVIDIA Omniverse platform, including OpenUSD (Universal Scene Description), Omniverse Nucleus, custom Kit Extensions, and Isaac Sim. Core Languages: Advanced programming proficiency in Python and solid working proficiency in C++ for building high-performance simulation modules and extensions. Cross-Discipline Simulation Competency: Demonstrated working knowledge and ability to guide technical integration across core simulation tracks: Distributed GPU infrastructure, containerization, and orchestration (Docker, Kubernetes, DGX, Ray, AWS/Azure). Scenario generation and robotics middleware (ROS2, DDS, SIL/HIL test harnesses).
Physics and rendering simulation (Omniverse RTX, PhysX, CUDA, synthetic sensor modeling for Camera/LiDAR/Radar). Automated testing and verification (CI/CD pipelines, regression suites, and determinism/KPI validation). Platform runtimes and SDK development (backend APIs, build/release tooling, distributed systems). AI-Native Engineering: Practical, daily experience utilizing AI-assisted developer workflows (LLM code generation, agentic development tools, and automated testing/debugging tools) to accelerate delivery. Desired Skills & Experience - Alternative Engine Experience: Prior hands-on experience building simulation or rendering pipelines in Unreal Engine 5 (UE5). Autonomous Systems & Sensor Modeling: Domain background in robotics, autonomous vehicles (AV), or ADAS, specifically building synthetic data generation pipelines for Camera, LiDAR, or Radar perception systems. Large-Scale GPU Cluster Orchestration: Practical experience configuring and optimizing distributed batch jobs
using Ray, Slurm, or NVIDIA DGX systems. Hardware-in-the-Loop Integration: Direct exposure to SIL/HIL testing environments, hardware interface testing, or real-time simulation hardware. Build Systems & Tooling: Familiarity with modern large-scale C++ build and packaging systems such as CMake or Bazel. Generative AI for Simulation: Hands-on experience integrating foundation models/LLMs directly into procedural generation pipelines (e.g., natural language-to-scenario generation or synthetic edge-case injection).