> Markdown version of [/jobs/ext/1198815-ai-engineer](https://www.wearedevelopers.com/jobs/ext/1198815-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - **Company:** The Yuki Company - **Location:** Antwerpen, Belgium - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** .NET Framework, Application Programming Interfaces (APIs), Artificial Intelligence, C Sharp (Programming Language), Python (Programming Language), Software Engineering, Generative AI, Backend, Machine Learning Operations, Virtual Agents, Api Design, Databricks - **Published:** July 8, 2026 - **Apply:** https://be.indeed.com/viewjob?jk=bf4f9390980c2a8c ## About the Role * Strong AI software engineering background (min 3 years), with real experience putting ML/AI into production at scale. * Hands-on with the stack: Python, Databricks, vector databases, MLflow (serving and monitoring side), and solid API design. * Comfortable with GenAI application patterns: RAG, agents, and orchestration (experience with an AI agent framework is a big plus) * A product-minded builder: you think about use cases, not just tickets, and can co-create with Product and Design. * Nice to have: C# (.NET), MLOps tooling, and experience building MCP for a tool or platform. * Fluent English is a must. ## Description It is our newest role, so you'll sit close to Product and Design, thinking like a mini product manager about where AI can add real value, then building it. If you get excited about agentic AI and want to shape where a product goes, this one's for you. * Build GenAI capabilities: Ship compound AI systems, retrieval-augmented features, and in-product prompt orchestration. * Productionize models: Own serving, APIs, runtime performance, and latency so AI lands reliably in the live app. * Serve retrieval: Build in-product vector search and retrieval integration, and be first response for model-quality regressions in production. * Land it in the product: Integrate AI predictions into the .NET backend alongside our backend engineers. * Co-create with Product: Spot new use cases, help shape the roadmap, and build features (including MCP-based capabilities) with Product and Design. ## Related Videos - [API Design - Getting Started](https://www.wearedevelopers.com/videos/33-api-design-getting-started) - [AI Agents & Agentic AI](https://www.wearedevelopers.com/videos/2017-ai-agents-agentic-ai) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Rest API Antipatterns](https://www.wearedevelopers.com/videos/100208-rest-api-antipatterns) - [Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure](https://www.wearedevelopers.com/videos/1532-agentic-ai-from-theory-to-practice-developing-multi-agent-ai-systems-on-azure) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix)