AI Engineer

Role overview

Responsibilities

• check_circle Develop artificial intelligence solutions (LLM applications, RAG architectures, agents, machine learning models).
• check_circle Design and develop AI assistants addressing business needs (chatbots, copilots, automations).
• check_circle Translate business requirements into concrete solutions, from prototyping to industrialisation.
• check_circle Leverage the capabilities of the Data Platform (Snowflake) and Generative AI tools to deploy reliable and scalable solutions.
• check_circle Integrate AI into business processes and the IT ecosystem.
• check_circle Develop the tests and guardrails required to ensure the reliability of AI solutions.
• check_circle Ensure compliance with AI governance frameworks and regulatory standards.
• check_circle Manage versioning, monitoring and performance tracking of deployed solutions.
• check_circle Rapidly prototype new use cases and integrate state-of-the-art developments.
• check_circle Continuously improve the robustness, reliability and scalability of AI pipelines.
• check_circle Work closely with the AI Product Owner and Data Engineering teams.
• check_circle Support business teams in identifying and adopting new use cases.
• check_circle Contribute to evaluating the value and impact of delivered solutions.

Basic qualifications

• Higher education degree in Computer Science, complemented by a specialisation or significant projects in Artificial Intelligence.
• Experience in developing and deploying artificial intelligence solutions.
• Strong expertise in GenAI (LLM, RAG, agents, prompting).
• Proficiency in Python, model and API integration, as well as leading LLMs (Claude, GPT, Mistral, etc.).
• Experience with Snowflake environments is a plus.
• Ability to understand business needs, challenge existing processes and build high-value solutions.
• Fluent English, both written and spoken.