Senior AI Engineer

Syensqo is all about chemistry. We’re not just referring to chemical reactions here, but also to the magic that occurs when the brightest minds get to work together. This is where our true strength lies. In you. In your future colleagues and in all your differences. And of course, in your ideas to improve lives while preserving our planet’s beauty for the generations to come. We are looking for:   We are looking for a senior AI Engineer to design, build, and productionize agentic and generative AI solutions on Azure, with a focus on real business outcomes, reproducibility, and maintainability (MLOps). The job holder  will co-lead the planning, execution, and delivery of AI proofs-of-value and products, ensuring they solve concrete business problems and can scale across Syensqo. The job holder is expected to  collaborate directly with stakeholders, guide technical decisions, and help shape patterns and standards for agentic AI within the enterprise.   We count on you for:   Assess and understand local specificities on the AI market - spot opportunities and potential partnerships with local AI leaders.   Working close to local leadership to provide AI solutions.   Lead the end-to-end design, implementation, and deployment of agentic and generative AI solutions (tool-using LLMs, function calling, multi-step workflows) that integrate with enterprise systems and data.   Architect RAG pipelines (retrieval, indexing, chunking, routing, safety filters, evaluation) using Azure services (e.g., Azure AI Search, Azure OpenAI / Azure AI Foundry, Azure Machine Learning) and modern frameworks.   Design, develop, and extend solutions across the Microsoft Copilot ecosystem, including Microsoft 365 Copilot, Copilot Studio, Copilot Agents, Azure AI Foundry Agents, and custom Copilot experiences. Build enterprise-grade copilots and agentic applications leveraging Microsoft Graph, Graph Connectors, Semantic Index, Copilot APIs, Power Platform, and Microsoft Fabric. Demonstrate expertise in integrating Copilot capabilities with business processes, enterprise knowledge sources, and line-of-business systems while ensuring governance, security, compliance, and responsible AI practices.   Drive MLOps on Azure: CI/CD for prompts and models, model/data/versioning, telemetry, guardrails, rollback strategies, canary releases, monitoring, and cost governance.   Serve as a technical authority on Azure (Azure ML, Azure DevOps, Azure Functions, Microsoft Fabric, Azure AI/OpenAI, Azure AI Search; familiarity with AKS/Container Apps is a plus).   Work side-by-side with business stakeholders in corporate functions and R&I to frame use cases, define success metrics, and deliver measurable value.   Champion Responsible AI: privacy, security, compliance, ethical use, and documentation across the lifecycle.   Mentor engineers/scientists, share best practices, and contribute reusable components, templates, and reference architectures.   Promote…