Principal AI Platform Engineer

We’re looking for a Principal Software Engineer to help build a platform that brings AI models into production. The product enables engineering teams to deploy and operate LLMs at scale, handling real-world traffic across multi-GPU and multi-node environments.

You’ll work at the intersection of Python development and AI infrastructure, making inference services faster, more efficient, and reliable in production. This is a hands-on role with ownership across development, deployment, and operations.
 

What you’ll do:

• Build Python services and tools for deploying and operating AI workloads.
• Scale and optimize LLM inference across multiple GPUs and compute nodes.
• Configure and tune model-serving frameworks such as vLLM.
• Improve inference performance, GPU memory usage, latency, and throughput.
• Automate infrastructure, deployment, and configuration workflows.
• Strengthen monitoring, testing, and production reliability.
• Troubleshoot complex issues across software and infrastructure.

What we’re looking for:

• Strong Python development experience.
• Hands-on experience running LLM inference services in production.
• Experience with multi-GPU and multi-node model deployment.
• Practical knowledge of vLLM or similar serving frameworks.
• Understanding of GPU memory constraints and inference optimization techniques.
• Experience with infrastructure automation and Infrastructure as Code.
• Strong Linux troubleshooting and production operations skills.

Nice to have: Distributed systems, Kubernetes, cloud infrastructure, networking, or experience building AI platforms and developer tools.