Your role As an AI Engineer, you will design, build and deploy AI-driven applications on Azure, working closely with business stakeholders and Solution Designers. You are expected to be hands-on, pragmatic, and able to move from prototype to production. Responsibilities Design and implement end-to-end AI solutions (from data ingestion to deployment) Build and deploy GenAI use cases (RAG, copilots, assistants, document processing) Develop and maintain APIs (e.G. FastAPI) integrating AI services into the ecosystem Deploy and manage applications on Azure (AKS, Azure ML, Functions, etc.) Work with LLMs (Azure Openai) and ensure proper orchestration and prompt design Ensure security, authentication and authorization flows between services (API-to-API, OAuth, SSO) Collaborate with other teams to integrate with internal systems and data platforms Contribute to CI/CD pipelines (GitHub / Azure DevOps) Optimize performance, scalability and cost of AI solutions Support the transition from PoC to industrialized production systems Tech environment (typical) Azure (Azure ML, Azure Openai, AKS, Functions, Storage) Python (FastAPI, ML/AI frameworks) Kubernetes (AKS) APIs & MicroServices architecture CI/CD (GitHub / Azure DevOps) Security protocols (OAuth2, SSO, managed identities) Data pipelines & integration with enterprise systems Profile Strong experience as AI Engineer / ML Engineer / Cloud Engineer (AI-focused) Hands-on experience with Azure cloud ecosystem Experience deploying AI/ML models into production environments Solid understanding of APIs, MicroServices and distributed systems Experience with LLMs / GenAI use cases is a strong plus Comfortable working in complex enterprise environments Ability to balance hands-on work and stakeholder interaction