Why This Role Stands Out
Advance your career by designing and building cutting-edge AI infrastructure for Generative AI and LLMs within a reputable firm, offering hybrid flexibility and significant growth opportunities. This role is perfect for experienced engineers with expertise in NVIDIA AI infrastructure and accelerated computing who are eager to shape the future of AI. Apply now to join a forward-thinking team and make a substantial impact.
Quick Overview
Job Description
Job Title: AI Senior Engineer / Senior AI Infrastructure Engineer
Location: Plano, TX (hybrid)
Job Summary
We are seeking an experienced Senior AI Infrastructure Engineer to design, build, and optimize next-generation AI infrastructure, GPU cloud platforms, and accelerated computing environments. The ideal candidate will have strong expertise in NVIDIA AI infrastructure, AI Factory architectures, GPUaaS, and high-performance computing.
The engineer will work on large-scale AI data center solutions supporting Generative AI, Large Language Models (LLMs), AI cloud platforms, and enterprise AI workloads. The role requires hands-on experience with NVIDIA reference architectures, DGX, HGX, Blackwell, GB200, Spectrum-X, and InfiniBand technologies.
Key Responsibilities
- Design and architect scalable AI infrastructure for enterprise AI, GenAI, and LLM workloads.
- Develop and implement AI Factory and GPUaaS (GPU as a Service) platforms.
- Design GPU-accelerated computing environments using NVIDIA reference architectures.
- Work with NVIDIA DGX, HGX, Blackwell GPU platforms, and GB200 systems.
- Architect high-performance GPU clusters and AI data center infrastructure.
- Design and optimize high-speed networking using NVIDIA Spectrum-X and InfiniBand.
- Support AI cloud and GPU cloud infrastructure deployment, integration, and operations.
- Collaborate with data center, cloud, networking, storage, and platform engineering teams.
- Evaluate infrastructure requirements for AI training, inference, and large-scale model deployment.
- Develop infrastructure standards, technical designs, and deployment documentation.
- Troubleshoot performance, scalability, networking, and infrastructure integration issues.
- Support capacity planning, resource utilization, and optimization of GPU infrastructure.
- Contribute to the design and implementation of LLM infrastructure and GenAI platforms.
- Work with engineering and architecture teams to evaluate emerging NVIDIA AI technologies.
Required Technical Skills
- Strong experience in AI Infrastructure and Accelerated Computing.
- Experience with AI Factory architecture and GPUaaS platforms.
- Strong knowledge of NVIDIA Reference Architecture.
- Hands-on experience with NVIDIA DGX and/or HGX systems.
- Experience with NVIDIA Blackwell architecture and/or GB200 platforms.
- Knowledge of NVIDIA Spectrum-X networking.
- Strong experience with InfiniBand networking and high-performance GPU clusters.
- Experience designing or supporting AI cloud, GPU cloud, or AI data center environments.
- Understanding of LLM infrastructure, Generative AI platforms, and AI workload deployment.
- Experience with infrastructure architecture, performance optimization, and system integration.
Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
- Experience with NVIDIA AI Enterprise, CUDA, or GPU software ecosystems.
- Experience with high-performance computing (HPC) and distributed AI workloads.
- Knowledge of GPU cluster management, containerized AI workloads, and cloud infrastructure.
- Experience with large-scale AI data center deployments.
- Strong analytical, problem-solving, and communication skills.
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