AI Engineer

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