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In Short

As Domain Architect for Non-Life Data & AI, I own the architecture across the full data and AI landscape of Nationale Nederlanden’s Dutch Non-Life business. Where my previous role as Solution Architect was centered around several platform (SIDAP & SIDIAP), this role operates across platforms, teams, and capability domains.

In practice, that means setting architectural direction for how data engineering, analytics, and AI capabilities evolve together. It means making calls on where platform boundaries sit, how AI workloads (from classical ML to agentic systems) get governed, and how cloud-native patterns land in a regulated enterprise context. It also means being the architectural counterpart to business and IT leadership when decisions cut across multiple domains.

A large part of the work is social. Aligning platform teams, data engineering squads, and AI initiatives around shared patterns and principles, while providing architectural guardrails that give teams enough structure to move fast without diverging. Will Larson’s Staff Engineer and his writing on what it means to be an architect capture this dynamic well. I wrote more about my own experience with it in Architecture Reflections: What do I do?.

On the technical side, we’re actively building out data- and AI-intensive applications as well as the underlying platforms. Use cases range from traditional ML pipelines to LLM-powered tooling and increasingly towards agentic systems that run parts of business processes autonomously. A key part of my role is maintaining the architecture runway: making sure the foundational decisions, platform capabilities, and integration patterns are in place before teams need them, so delivery doesn’t stall waiting for architecture to catch up. That also means working closely with central enterprise architecture to ensure domain-level choices align with organization-wide strategy, standards, and cross-domain concerns.

I’m aware that descriptions like these can read a bit abstract. Architecture roles tend to sit at a level where things sound vague precisely because they cut across so many areas. If you read this and thought “I’m not sure what that actually means in practice,” that’s a fair reaction and I’d genuinely welcome the question. You can find me on LinkedIn or drop me an email.