About this role
Responsibilities Design and implement AI-powered applications using LLMs , RAG , and agentic workflow patterns. Build backend services, APIs, and integrations required for AI-centric applications. Optimize retrieval pipelines including chunking, embeddings, vector search, and hybrid search. Implement evaluation, testing, monitoring, and observability frameworks for AI-driven solutions. Collaborate with stakeholders to define safe patterns for tool use and human-in-the-loop workflows. Troubleshoot complex issues including hallucinations, poor retrieval quality, and high latency. Requirements You bring 5+ years of software engineering experience, preferably in backend or full-stack development. You possess 1+ years of experience integrating LLMs or other generative AI services into software applications. You have practical knowledge of RAG , embeddings, vector search, and retrieval quality improvement. You have strong programming skills in Python . You possess experience with MCP , A2A , tool calling, or multi-agent workflows. You have experience designing maintainable services with CI/CD , logging, and deployment practices. You bring a solid understanding of cloud-native application development and security-conscious design. You're able to evaluate AI application quality using test datasets and regression testing metrics. You are fluent in English with active knowledge of French or Dutch . Nice to Haves Experience with AI frameworks such as LangGraph , LangChain , or Semantic Kernel . Familiarity with the Azure cloud environment and its AI ecosystem tools. Experience with backend development in .NET or C# . Knowledge of vector databases or enterprise search platforms. Experience working in regulated or security-sensitive enterprise environments.