AI Engineer/Developer

Role: AI Engineer/Developer

Location: brussels BE

Langugae: French/Dutch

• Design and implement AI-powered applications using LLMs, RAG, and agentic workflow patterns.
• Build backend services, APIs, and integrations needed for AI-centric applications.
• Design and improve retrieval pipelines, including chunking, embeddings, vector search, hybrid search, metadata filtering, and reranking.
• Work with LLM APIs and AI orchestration frameworks to build reliable workflows.
• Implement evaluation, testing, monitoring, and observability for AI applications.
• Help define safe and practical patterns for tool use, human-in-the-loop approval, and agentic behavior.
• Collaborate with other engineers and product/business stakeholders.
• Support model and framework selection based on quality, cost, latency, maintainability, and security.
• Help troubleshoot issues such as hallucinations, poor retrieval quality, high latency, cost inefficiency, and unreliable outputs.

Requirements:

• You are able to speak, read and write fluently English and French or Dutch.
• Minimum 5 years of experience as Software Engineer, preferably in backend or full-stack development.
• Minimum 1 to 2 years of experience integrating LLMs or other generative AI services into software applications.
• Practical knowledge of RAG, embeddings, vector search, and retrieval quality improvement.
• Strong programming skills in Python.
• Experience with MCP, A2A, tool calling, or multi-agent workflows.
• Experience designing maintainable services with proper testing, logging, CI/CD, and deployment practices.
• Understanding of AI application evaluation, including test datasets, quality metrics, regression testing, and user feedback.
• Good understanding of cloud-native application development.
• Security-conscious mindset when working with internal or sensitive data.
• Ability to communicate technical trade-offs clearly and pragmatically.
• Ability to distinguish when AI, RAG, or agents are useful and when a simpler deterministic solution is better.
• Nice to Have
• Experience with AI frameworks such as LangGraph, LangChain, Semantic Kernel.
• Experience with observability or evaluation tools.
• Familiarity with Azure cloud environment.
• Experience with Microsoft AI ecosystem tools such as Semantic Kernel, Microsoft
• Agent Framework, Microsoft Foundry, or Microsoft 365 Agents SDK.
• Experience with .NET / C#.
• Experience with vector databases or enterprise search platforms.
• Experience working in regulated, security-sensitive, or enterprise environments.
• The 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.