AI Architect

About the role

We are seeking an AI Architect to lead the design and delivery of scalable, secure, and high‑performance AI solutions on Microsoft Azure. You will shape our AI strategy, define end‑to‑end architectures for data platforms, machine‑learning models, and large language model integrations, and support engineering teams in building production‑ready services.

Key responsibilities

• Design and implement end‑to‑end AI/ML architectures on Azure using services such as Azure Machine Learning, Azure OpenAI, Azure Cognitive Services, Azure Data Lake, Azure Synapse, and Azure Data Factory.
• Define architecture for LLM‑based applications, including retrieval‑augmented generation, fine‑tuning, and embeddings.
• Establish data ingestion, transformation, and serving pipelines.
• Ensure best practices for security (RBAC, private endpoints, data protection), scalability (containerization, Kubernetes, AKS), and cost optimization.
• Define MLOps frameworks and Azure‑based CI/CD pipelines.
• Provide technical guidance and governance to engineering teams on architecture patterns and standards.
• Evaluate and recommend emerging AI technologies, tools, and frameworks.

Required profile

• Bachelor's or Master's degree in Computer Science, AI, or a related field.
• 7+ years of experience in software or data architecture with hands‑on AI/ML system delivery.
• Professional working proficiency in English.

Required skills

• Azure AI services (Azure Machine Learning, Azure OpenAI, Azure Cognitive Services, Azure Data Lake, Azure Synapse, Azure Data Factory).
• LLM frameworks such as LangChain and Semantic Kernel.
• MLOps tools including MLflow and Azure ML pipelines.
• Programming languages: Python, C#.NET/.NET Core.
• API design and microservices architecture.
• Containerization, Kubernetes, Azure Kubernetes Service (AKS).
• Security controls: RBAC, private endpoints, data protection.
• CI/CD pipeline implementation.

What we offer

• Permanent contract (CDI).
• Meal vouchers and DKV insurance.
• Possibility of a company car.
• Hybrid work model with 1‑2 remote days per week.
• Continuous learning and career development opportunities.