LLM Inference GPU Systems Consultant

Delan Associates, Inc; Charlotte (NC); On-site; USD 150,000 - 210,000; Full time

Job summary

Delan Associates, Inc. in Charlotte, NC is seeking an LLM Inference & GPU Systems Consultant to build and maintain on-prem LLM infrastructure on NVIDIA H200 clusters with an OpenShift AI deployment.

The role focuses on production inference, not training, requiring onsite presence 3 days/week and hands-on optimization of GPU workloads, vLLM, TensorRT-LLM, and Hugging Face lifecycle. Candidates should have 8+ years in LLM systems or AI infra, experience with OpenShift AI and RunAI, and strong

Qualifications

• 8+ years of experience as an LLM Systems Engineer or AI Infrastructure Runtime Engineer.
• Hands-on experience with NVIDIA H200 clusters and runtime optimization (KV Cache, prefill/decode).
• Proficiency with OpenShift AI and RunAI for GPU orchestration.
• Experience with modern inference frameworks: vLLM and TensorRT-LLM.
• Experience managing the Hugging Face deployment lifecycle.

Responsibilities

• NVIDIA GPU Runtime Optimization: Drive runtime efficiency and optimize token generation with prefill/decode and KV cache management.
• Inference Serving: Deploy and manage inference engines including vLLM and TensorRT-LLM.
• Hardware Utilization: Optimize GPU throughput, batching, latency; manage RunAI and Kubernetes GPU orchestration.
• Model Lifecycle Management: Oversee Hugging Face model onboarding, deployment, retirement.
• Platform Operations: Operate and maintain the OpenShift AI ecosystem as the primary container platform for GenAI workloads.

Skills

LLM Systems Engineer

AI Infrastructure Runtime

Runtime optimization

GPU orchestration

OpenShift AI

RunAI

vLLM

TensorRT-LLM

Hugging Face lifecycle

Tools

NVIDIA H200 GPUs

OpenShift AI

RunAI

Kubernetes GPU orchestration

vLLM

TensorRT-LLM

Job description

Job Title: LLM Inference & GPU Systems Consultant

Location: Charlotte, NC (Onsite)

Duration: 6+ Months

Must be onsite at client in Charlotte, NC at least 3 days/week

Role Overview

We are seeking an AI Infrastructure Runtime Engineer to build and maintain large-scale on-prem LLM infrastructure. This is an enterprise private GenAI environment running on NVIDIA H200 GPU clusters and an OpenShift AI deployment ecosystem. You will manage production inference internally, including self-hosting open-source LLMs like Llama. We are focused exclusively on inferencing; this role involves no model training infrastructure or fine-tuning pipelines.

Key Responsibilities

• NVIDIA GPU Runtime Optimization: Drive extreme runtime efficiency and optimization for the token generation pipeline. Specifically manage prefill/decode optimization and KV cache management.
• Inference Serving: Deploy and manage inference engines including vLLM and TensorRT-LLM.
• Hardware Utilization: Optimize GPU throughput tuning, batching strategies, and latency optimization. Manage workload orchestration using RunAI and Kubernetes GPU orchestration.
• Model Lifecycle Management: Oversee the complete Hugging Face model lifecycle, including model onboarding, deployment, and retirement.
• Platform Operations: Operate and maintain the OpenShift AI ecosystem as the primary container platform for GenAI workloads.

Required Qualifications

• 8+ years experience working as an LLM Systems Engineer or AI Infrastructure Runtime Engineer.
• 8+ years hands-on experience with NVIDIA H200 clusters and runtime optimization techniques (KV Cache, prefill/decode).
• Proficiency in OpenShift AI and GPU orchestration tools like RunAI.
• Strong experience with modern inference frameworks, specifically vLLM and TensorRT-LLM.
• Proven track record managing the Hugging Face deployment lifecycle.