AI Cloud Engineer Job Description

For a client we are seeking a highly skilled and motivated AI Cloud Engineer to join a dynamic AI department. This role is pivotal in driving the implementation and optimization of AI and Generative AI-based applications on Microsoft Azure. The successful candidate will work in an environment that presents opportunities to apply analytical skills to solve business problems.

Key Responsibilities:

• Serve as the AI reference in designing and implementing cloud-based architectures dedicated to AI and Generative AI applications on Microsoft Azure.
• Develop and deploy scalable AI and Generative AI models into production environments.
• Collaborate with data scientists and AI researchers to integrate machine learning models into cloud infrastructure.
• Ensure the reliability, scalability, and security of AI applications.
• Automate the deployment, monitoring, and maintenance of AI models and services.
• Stay updated with the latest advancements in AI, Generative AI, and cloud technologies to continuously improve systems.
• Troubleshoot and resolve issues related to cloud infrastructure and AI model deployment.

Mission Period:

• Expected Start Date: As soon as possible
• Duration: 24 months (extension possible depending on project evolution)

Language Requirements:

• English, Dutch and French

Level of Education Required:

University degree in Computer Science, Engineering, or a related field.

Required Knowledge and Experience:

Personal Skills:

• Excellent problem-solving skills.
• Ability to work in a fast-paced environment.
• Strong communication and collaboration skills.

Technical Experience Required:

• Cloud Expertise: Strong knowledge of cloud platforms, especially Azure (Azure ML, Vertex AI, Databricks, Azure OpenAI, etc.).
• Software Engineering: Solid background in application development, API integration, and frontend integration, following security best practices (experience with FastAPI and Asyncio is a plus).
• Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes).
• Experience with AI and Generative AI frameworks (e.g., TensorFlow, PyTorch, GPT).
• Gen AI Deployment: Proven experience in deploying and monitoring Gen AI models using CI/CD pipelines, Weight & Biases, and GitHub workflows.

Functional Experience Required:

• Proven experience as a Cloud Engineer, MLOps Engineer, or similar role.
• Strong understanding of cloud-based architecture, particularly on Microsoft Azure.
• Experience in deploying and managing AI and Generative AI applications in production.