Senior On-Premise LLM Inference & GPU Systems Consultant

Charlotte, NC, US • Posted 1 day ago • Updated 18 minutes ago
Contract Corp To Corp
Contract W2
On-site
$68709$2/-
Fitment

Dice Job Match Score™

⏳ Almost there, hang tight...

Job Details

Skills

  • Cloud-Infrastructure-AWS Networking-3rd Party Tools

Summary

TECHNOGEN, Inc. is a Proven Leader in providing full IT Services, Software Development and Solutions for 15 years.

TECHNOGEN is a Small & Woman Owned Minority Business with GSA Advantage Certification. We have offices in VA; MD & Offshore development centers in India. We have successfully executed 100+ projects for clients ranging from small business and non-profits to Fortune 50 companies and federal, state and local agencies.


Senior On-Premise LLM Inference & GPU Systems Engineer

Location: Charlotte, NC (Onsite)

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
Deep expertise as an LLM Systems Engineer or AI Infrastructure Runtime Engineer.
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.

Best Regards

Govinda rajulu. M| Sr. Talent Acquisition Specialist

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10217412
  • Position Id: 2026-43231
  • Posted 1 day ago
Create job alert
Set job alertNever miss an opportunity! Create an alert based on the job you applied for.

Similar Jobs

Hybrid in Charlotte, North Carolina

5d ago

Easy Apply

Contract, Third Party

Depends on Experience

Charlotte, North Carolina

27d ago

Easy Apply

Full-time, Third Party

130000 - 140000

Charlotte, North Carolina

Today

Full-time

Charlotte, North Carolina

Today

Full-time

Search all similar jobs