Senior Software & Data Engineer

As our Senior Software & Data engineer, you’ll take broad technical ownership across the full software development lifecycle, from architecture and hands-on development through deployment, monitoring and scaling.

What you’ll do

• Act as the technical partner to the client: translate business problems into solutions, shape scope, explain trade-offs
• Own the architecture on client engagements: design the solution, then defend and refine it with the client’s IT and security teams
• Hands-on backend development through to production deployment
• Design and build the data platform underneath: layered bronze/silver/gold architecture and reliable pipeline
• Architect and integrate GenAI capabilities (LLM APIs, RAG, agentic components) into production applications with the engineering team
• Help shape how Merlin builds, the standards, tooling and technology choices we adopt, and grow the engineers around you

• Solid software engineering experience, with real depth on the backend
• Experience owning architecture end to end and taking systems into production
• Hands-on experience building or substantially working on a layered data platform (bronze/silver/gold)
• Cloud experience: Azure is ideal, AWS or GCP transfers fine
• Comfortable and credible in front of clients - you can convince a technical stakeholder you know what you’re doing, and back it up
• 4+ years of experience
• Based in Belgium (or willing to relocate before joining) and legally authorized to work in Belgium.
• Fluent English

Strong pluses:

• You took a GenAI project to production (an agent or a RAG system), running for real users
• Experience leading or mentoring a team of engineers
• Python, and API design at scale
• Some frontend ability (TypeScript with React or Vue), enough to be dangerous, not necessarily a specialist
• CI/CD and containerised deployment; Azure DevOps or GitHub Actions
• Dutch or French

Merlin Innovation is an AI consultancy building enterprise-grade, production-deployed applications for clients across a range of industries. Increasingly, these are AI-native products: LLM-powered features, retrieval pipelines (RAG), and agentic workflows running in production.