Solution Architect AI

We ARE Renewables is looking for a Solution Architect AI for one of our clients in the energy sector. Due to the energy transition, we are facing more work than ever before. The sustainability of energy sources leads to a wide variation in supply and demand, with the challenge of maintaining high delivery reliability. Increasing electrification leads to congestion in the grids, preventing new customers from being connected and existing customers from growing. The strategic challenge for the client is therefore clear: expand the energy grid as quickly as possible and ensure that the available capacity on the grid is utilized optimally Task and Responsibilities

• Inventory & Analysis:

• Mapping the current technologies and AI initiatives
• Identifying technological gaps and future short- and long-term needs.

• Architectural design

• Designing an AI Foundation framework that is scalable, secure, and efficient, and aligns with the clients enterprise architecture and cloud strategy.
• Integration with existing platforms such as the EMS, SAP, and the data platform.

• Technology Selection & Roadmap:

Advising on tooling, platforms, and infrastructure suitable for the clientss IT landscape. Developing a roadmap for the adoption and implementation of AI capabilities, including governance and lifecycle management.

• Collaboration & Knowledge Sharing:

• Working in close collaboration with existing data scientists, data engineers, ML engineers, security officers, enterprise architects, and business stakeholders.

• Knowledge sharing and coaching of teams on AI best practices and architecture principles.

• You have a higher professional or university (HBO) working and thinking level in a relevant field such as Information Technology, (Business) Informatics, Mathematics, etc.
• You have demonstrable experience (at least 3 years) as a system or solution architect in an agile environment.
• Hands-on experience with cloud platforms such as Microsoft Azure, including Azure ML, Databricks, Synapse, Data Factory, and Purview.
• In-depth knowledge of data architecture and AI solutions in a regulated sector, preferably within energy, infrastructure, or public services.
• Experience with MLOps: model lifecycle management, CI/CD for ML, monitoring, and governance.
• Trend-aware: follows developments such as generative AI, predictive maintenance, digital twins, and AI-driven grid optimization.
• Security & compliance: familiar with GDPR, NIS2, and sector-specific requirements such as those of ACM and Netbeheer Nederland.
• Framework architect: experience setting up AI foundations including data lakehouses, feature stores, model registries, and governance layers.