Principal Inference Software Engineer

Optomi; Plano (TX); On-site; USD 170,000 - 250,000; Full time

Job summary

Optomi, in partnership with a large telecommunications company, seeks a Principal Inference Software Engineer to join their Plano, TX team. You will build, deploy, and scale production AI inference infrastructure across Kubernetes, vLLM, Python, GPUs, and cloud/on-prem environments.

In this role you will optimize model serving, manage GPU resources, and develop automation to support both R&D and production workloads. A strong background in distributed systems and reliability is essential.

Qualifications

• Strong software engineering and Python skills.
• Production experience with LLM inference/model serving, ideally vLLM.
• Experience with GPU infrastructure, containers, and CI/CD.
• Understanding of scaling, automation, observability, and reliability for distributed systems.
• Experience with cloud and/or on-prem infrastructure preferred.

Responsibilities

• Build and operate LLM inference infrastructure at scale.
• Deploy models with vLLM and Kubernetes.
• Develop Python automation for deployment, scaling, updates, rollbacks, and health monitoring.
• Manage GPU capacity, performance, reliability, and production workloads.
• Build tools to simplify model deployment for engineers.
• Support R&D and production inference environments.
• Troubleshoot and optimize model-serving performance.

Skills

Python

Software engineering

LLM inference

Model serving

vLLM

GPU infrastructure

Containers

CI/CD

Observability

Distributed systems

Cloud/On-prem

Tools

Kubernetes

Docker

CI/CD tooling

Job description

Optomi, in partnership with a large telecommunications company, is seeking a Principal Inference Software Engineer to join their team in the Plano, TX Area. The ideal candidate will have experience building, deploy, and scale production AI inference infrastructure. You’ll work across Kubernetes, vLLM, Python, GPUs, and cloud/on-prem environments to make model serving reliable, scalable, and highly automated.

What The Right Professional Will Enjoy

• Building and operating LLM inference infrastructure at scale.
• Deploying and managing models using vLLM and Kubernetes.
• Developing Python automation for model deployment, scaling, updates, rollbacks, and health monitoring.
• Managing GPU capacity, performance, reliability, and production workloads.
• Building tools that allow engineering teams to deploy and access models without managing underlying infrastructure.
• Supporting both R&D and production inference environments.
• Troubleshooting and optimizing model-serving performance and reliability.

Apply Today If Your Background Includes

• Strong software engineering and Python skills.
• Production experience with LLM inference/model serving, ideally vLLM.
• Experience with GPU infrastructure, containers, and CI/CD.
• Understanding of scaling, automation, observability, and reliability for distributed systems.
• Experience with cloud and/or on-prem infrastructure preferred.