Generative AI Infrastructure Engineer

Job Description

We are looking for a technical professional to support the development and evolution of the generative infrastructure of Nexum products. The person will work on local and cloud inference, open-weight model deployment, runtime management, caching, batching, containerization, observability and performance optimization. Tech Stack: Python, Docker, Kubernetes, vLLM, Ollama, llama.cpp, MLX, PostgreSQL, Redis, OpenTelemetry, Llama, Qwen, Mistral, Gemma, DeepSeek, Phi. Key Responsibilities: - Manage and optimize LLM model deployment in production environments - Configure inference runtimes (vLLM, Ollama, llama.cpp, MLX) - Implement caching, batching and load balancing strategies - Containerize and orchestrate AI services with Docker and Kubernetes - Monitor performance with OpenTelemetry and observability tools - Optimize GPU/CPU resource usage for inference This job posting is addressed to both genders, in compliance with laws 903/77 and 125/91 on equal treatment in the workplace and against gender discrimination. We welcome candidates of all ages and nationalities, in accordance with legislative decrees 215/03 and 216/03. Nexum also encourages applications from people with disabilities, in compliance with current regulations.

What You Bring

• AI Infrastructure

  Experience with vLLM, Ollama, llama.cpp, MLX and inference runtimes

• Containers & Orchestration

  Docker, Kubernetes, containerization and model deployment

• Observability

  OpenTelemetry, monitoring, logging and performance optimization

• Database & Caching

  PostgreSQL, Redis, caching and batching strategies