DevSecOps Engineer for AI/LLM Project

- Proven experience in a DevOps, Platform Engineering, or Infrastructure Engineering role supporting production environments - Strong experience working with Linux-based systems, including shell scripting (Bash) and VM administration - Hands-on experience running and supporting containerised services using Docker, with the ability to read, understand, and modify Docker configurations - Ability to support and troubleshoot AI/LLM-powered applications in production or pre-production environments - Experience operating multi-container environments supporting backend services such as databases, vector stores, or inference engines - Solid understanding of CI/CD pipelines, with practical experience using GitLab, including pipeline configuration and environment variables - Strong working knowledge of Git and source code management best practices - Experience configuring and maintaining NGINX (or equivalent) as a reverse proxy for backend services and web applications - Experience standing up and managing infrastructure using Infrastructure as Code tools (e.g. Terraform) - Proficiency in Python, including supporting backend services, scripts, or LLM application frameworks - Experience working with relational databases (e.g. PostgreSQL), including deployment, configuration, and operational support - Comfortable working across multiple projects at different stages of delivery, supporting shared platforms used by multiple teams - Strong problem-solving skills with the ability to debug infrastructure, CI/CD, and application-level issues - Ability to collaborate effectively with Data Science, AI, and Engineering teams, understanding boundaries between infrastructure, inference, and model training responsibilities - Support and scale the AI platform to run multiple LLM-based projects across varying levels of maturity and technical stacks