Ingénieur IA

Role overview

Principal responsibilities

• Design, develop, test, and improve enterprise AI agents using Microsoft Copilot Studio, Azure AI Foundry, Databricks, and related technologies.
• Translate ambiguous business opportunities into architectures, technical requirements, delivery plans, and measurable acceptance criteria.
• Develop data-grounded architectures and RAG solutions connecting language models to enterprise content, data, applications, and processes.
• Integrate agents securely with APIs, systems, events, workflows, identity systems, and approved content sources.
• Implement tool use, orchestration, memory, structured outputs, human approvals, reusable components, and production standards.
• Build evaluation and testing methods for quality, retrieval, task completion, hallucination risk, security, latency, cost, and business outcomes.
• Apply responsible AI, privacy, cybersecurity, intellectual property, retention, access-control, auditability, and human-oversight practices.
• Lead design and code reviews, create technical documentation, collaborate with multidisciplinary teams, and transfer solutions to support teams.

Technical capabilities

• Production experience with generative AI, AI agents, RAG, or machine learning is required.
• Strong Python, API development, automated testing, version control, and modular design skills are required.
• Experience with prompt engineering, model selection, data grounding, tool use, orchestration, memory, and structured outputs is required.
• Experience with document ingestion, embeddings, vector databases, hybrid search, and retrieval-quality evaluation is required.
• Experience with secure enterprise integrations and AI deployment and troubleshooting in Azure or a comparable cloud environment is required.

Experience required

• Approximately 7 or more years of experience in software engineering, machine learning engineering, AI engineering, or a related field.
• Approximately 3 or more years delivering AI or machine learning solutions beyond proof of concept.
• Practical experience with Python, REST APIs, Git, and cloud application development.
• Experience with language-model APIs and Semantic Kernel, LangChain, AutoGen, or an equivalent orchestration or agent framework.
• Demonstrated enterprise AI agent development using Microsoft Copilot Studio, Azure AI Foundry, and Databricks.
• Experience deploying AI agents and implementing evaluation, monitoring, security, RAG, vector database, or enterprise search capabilities.
• Ability to work with business stakeholders, explain technical trade-offs, challenge assumptions, mentor others, and influence multidisciplinary teams.