Software Engineer with Experience in developing AI-centric applications

ph3Software Engineer with Experience in developing AI-centric applications /h3 pBrussels /p pWe are looking for a Software Engineer Service to join one of our software engineering teams focused on developing AI-centric applications. /p pThe role combines strong software engineering skills with practical experience in building solutions using LLMs, RAG, AI assistants, and agentic workflows. The ideal candidate can help design, implement, evaluate, and improve AI-powered applications that are reliable, secure, maintainable, and useful in a real business environment. /p pThis is a hands-on engineering role. We are looking for someone who can build production-quality solutions, contribute to technical direction, and support the team in applying AI engineering practices effectively.br/ /p pbTasks: /b /p ul liDesign and implement AI-powered applications using LLMs, RAG, and agentic workflow patterns. /li liBuild backend services, APIs, and integrations needed for AI-centric applications. /li liDesign and improve retrieval pipelines, including chunking, embeddings, vector search, hybrid search, metadata filtering, and reranking. /li liWork with LLM APIs and AI orchestration frameworks to build reliable workflows. /li liImplement evaluation, testing, monitoring, and observability for AI applications. /li liHelp define safe and practical patterns for tool use, human-in-the-loop approval, and agentic behavior. /li liCollaborate with other engineers and product/business stakeholders. /li liSupport model and framework selection based on quality, cost, latency, maintainability, and security. /li liHelp troubleshoot issues such as hallucinations, poor retrieval quality, high latency, cost inefficiency, and unreliable outputs. /li /ul pbRequirements: /b /p ul liYou are able to speak, read and write fluently English and French or Dutch. /li liMinimum 5 years of experience as Software Engineer, preferably in backend or full-stack development. /li liMinimum 1 to 2 years of experience integrating LLMs or other generative AI services into software applications. /li liPractical knowledge of RAG, embeddings, vector search, and retrieval quality improvement. /li liStrong programming skills in Python. /li liExperience with MCP, A2A, tool calling, or multi-agent workflows. /li liExperience designing maintainable services with proper testing, logging, CI/CD, and deployment practices. /li liUnderstanding of AI application evaluation, including test datasets, quality metrics, regression testing, and user feedback. /li liGood understanding of cloud-native application development. /li liSecurity-conscious mindset when working with internal or sensitive data. /li liAbility to communicate technical trade-offs clearly and pragmatically. /li liAbility to distinguish when AI, RAG, or agents are useful and when a simpler deterministic solution is better. /li liNice to Have /li liExperience with AI frameworks such as LangGraph, LangChain, Semantic Kernel. /li liExperience with observability or evaluation tools. /li liFamiliarity with Azure cloud environment. /li liExperience with Microsoft AI ecosystem tools such as Semantic Kernel, Microsoft /li liAgent Framework, Microsoft Foundry, or Microsoft 365 Agents SDK. /li liExperience with .
NET / C#. /li liExperience with vector databases or enterprise search platforms. /li liExperience working in regulated, security-sensitive, or enterprise environments. /li liThe right consultant should be comfortable working across software engineering, AI integration, evaluation, security, and production readiness. They should be able to move fast when building MVPs, while still applying enough engineering discipline to make successful solutions scalable and maintainable. /li /ul /p