LLM Infrastructure Engineer

We are looking for a Senior Python / AI API Engineer to build and deploy production-grade services powering Large Language Model (LLM) applications. This role focuses on developing high-performance APIs for model inference, optimizing GPU workloads, and deploying AI services in cloud environments.

This is an engineering-focused role, not research. We are looking for someone who has built and shipped AI systems into production and understands the challenges of scalable inference and model serving.

Key Responsibilities

• Develop high-performance APIs using Python (3.10+) and FastAPI
• Build and deploy LLM inference services using HuggingFace Transformers and PyTorch
• Optimize GPU workloads and CUDA memory usage
• Implement streaming inference APIs for real-time model responses
• Containerize and deploy services using Docker and GPU-enabled infrastructure
• Deploy AI workloads in Azure environments (AKS, ACI, or Container Apps)

Required Skills

• Strong Python development experience (3.10+)
• Hands-on experience building production APIs with FastAPI
• Experience with HuggingFace Transformers and PyTorch
• Solid understanding of REST API design
• Experience deploying containerized applications with Docker

Nice to Have

• Experience with OpenAI-compatible APIs, vLLM, or Text Generation Inference (TGI)
• Experience deploying AI workloads on Azure GPU infrastructure
• Familiarity with LoRA / PEFT fine-tuning
• Exposure to legal or financial NLP use cases

Ideal Candidate: A hands-on engineer who understands how LLM systems run in production-from model loading and tokenization to GPU deployment and scalable APIs.