Senior AI Platform Engineer
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- Stated location
- United States
- Listing updated on our site
- 14 Nov 2026, 04:01 EAT
- Mentions "eat"
- Timezone range utc-10 to utc+14 overlaps EAT (UTC+3)
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| Employer | Verified Direct Employer (Protected) |
|---|---|
| Location | United States |
| Remote type | Full Time |
| Posted | 2h ago |
| Application Status | Pro Membership & Free Pass Access |
About this role (Direct Employer Details Protected)
Get Set for [Employer]!
Join our team of student-focused individuals working together in order to encourage intellectual and spiritual growth, leadership and service.
CURRENT STUDENT or EMPLOYEE? Please log into Workday and use the Career Tile to find and apply to jobs from our internal career sites.
Senior AI Platform Engineer
ENTERPRISE AI INFRASTRUCTURE & LLM OPERATIONS
Department: Information Technology | Employment Type: Full-Time | Location: Remote, with occasional travel to main campus (Williamsburg, KY) as needed
Help Us Build What’s Next in AI
At the [Employer], we’re building a new enterprise AI environment that brings powerful, locally hosted AI technologies to students, faculty, and staff. We’re looking for a Senior AI Platform Engineer who enjoys building from the ground up, tackling challenging engineering problems, and shaping how AI works in higher education.
You’ll help design, deploy, and grow an on-premises environment powered by NVIDIA GPU infrastructure and NVIDIA AI Enterprise, supporting large language models (LLMs), high-performance inference, and secure APIs. You’ll partner with infrastructure, cybersecurity, enterprise applications, and our emerging AI Lab to turn ambitious ideas into dependable services.
What You’ll Do
- Build the foundation. Design, deploy, and manage on-premises and hybrid AI infrastructure, including NVIDIA GPU environments and NVIDIA AI Enterprise.
- Bring models to life. Deploy, optimize, and maintain locally hosted LLMs and inference services using NVIDIA NIM, vLLM, Ollama, or comparable tools.
- Make AI accessible. Build secure APIs and services connecting approved AI capabilities to [Employer] applications and users.
- Keep things running. Monitor performance, optimize GPU resources, troubleshoot issues, and maintain security, reliability, and scalability.
- Automate and improve. Use Linux, containers, scripting, and platform engineering practices to streamline operations.
- Collaborate and shape what’s next. Partner across IT and the AI Lab, evaluate emerging technologies, and influence platform architecture.
What You’ll Bring
- Significant professional experience in platform engineering, DevOps, systems engineering, or enterprise infrastructure, including demonstrated responsibility for deploying and supporting production AI/ML environments.
- Hands-on experience deploying or administering NVIDIA GPU-based AI infrastructure, NVIDIA AI Enterprise, NVIDIA NIM, or comparable AI/ML and enterprise inference platforms.
- Strong Linux, networking, containers, and modern infrastructure knowledge.
- Scripting and automation experience with Python, Bash, or similar tools.
- Familiarity with APIs, authentication, security, and monitoring; strong troubleshooting and collaboration skills.
- Bachelor’s degree in a related technical field or equivalent professional experience.
Even Better If You Have
- Direct experience with NVIDIA AI Enterprise and NVIDIA NIM; CUDA or GPU performance optimization.
- Experience with vLLM, Ollama, Hugging Face, Docker, Kubernetes, infrastructure as code, or CI/CD.
- Knowledge of MLOps/LLMOps, vector databases, embeddings, or retrieval-augmented generation (RAG).
- Experience with enterprise API gateways, hybrid cloud, higher education, or research computing.
Why This Role Is Different
- Build from the beginning. Help establish a new AI platform and shape its long-term direction.
- Work with powerful technology. Get hands-on with NVIDIA GPU computing, enterprise AI software, and open-weight language models.
- Make an impact. Support teaching, learning, research, and institutional innovation.
- Have a voice. Help choose tools, set technical standards, and improve the platform as it grows.
Let’s Build Something Great
We’re looking for an experienced engineer who brings deep technical expertise, strong problem-solving skills, and a proven ability to design, deploy, and manage enterprise AI infrastructure.
The ideal candidate has hands-on experience with GPU-accelerated computing, locally hosted large language models, and production AI platforms, along with the technical judgment to lead complex implementations from the ground up.
If you’re ready to bring your expertise to an exciting new initiative and help establish the foundation for enterprise AI at the [Employer], we’d love to hear from you.
[Employer] is different by design. Our employees exemplify our motto in the pursuit of a
“life-more-abundant.”
Originally posted on [Employer]
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