Solution Architect

• You work within a team focused on Artificial Intelligence & Innovation.
• This team develops a generic, sovereign AI platform with reusable AI building blocks, such as RAG and agentic AI.
• You ensure technical coherence within this landscape.
• You translate needs and developments into concrete architecture choices and solution directions.
• You look at the whole: from AI models and inference to data, APIs, identity & access management, security, monitoring, and the underlying infrastructure.
• You design and monitor the solution architecture of the generic AI platform and its associated AI building blocks.
• You translate functional and technical needs into architecture principles, technical frameworks, and feasible solution directions.
• You make architecture choices regarding, among other things, AI models, inference, RAG, agentic AI, APIs, data, and infrastructure.
• You monitor the coherence between the AI platform, AI solutions, and the organization's existing architectures and provisions.
• You weigh public cloud, private cloud, and on-premises provisions, with attention to digital sovereignty, security, privacy, scalability, and manageability.
• You guide engineers and development teams in translating architecture into concrete technical implementations.
• You investigate which provisions can be offered generically so that multiple teams can use them.
• You recognize patterns in individual solutions and translate them into reusable building blocks and architecture principles.
• You follow developments in Generative AI, open-weight models, RAG, agents, inference, and AI infrastructure.
• You assess what these developments technically mean for the AI platform and translate relevant developments into concrete architecture choices.
• You oversee how AI relates to data, integration, security, infrastructure, and existing provisions.
• You collaborate with domain and enterprise architects, security specialists, engineers, and other experts inside and outside the organization.
• You can substantiate technical choices and bring different disciplines together.

What they ask

• HBO/WO (higher professional education/university) work and thinking level, for example in computer science, technical computer science, or a comparable field.
• Extensive relevant experience with IT architecture and designing complex IT solutions.
• Experience with solution architecture, software architecture, platform architecture, or similar activities.
• Experience with solution architecture, software architecture, platform architecture, or similar activities.
• Knowledge of modern cloud, platform, and integration architectures, including APIs, identity & access management, and security.
• Ability to analyze complex technical issues and translate them into coherent architecture choices and concrete solution directions.
• Ability to connect architecture with technical realization and effectively collaborate with engineers, development teams, and other architects.
• Sufficient in-depth knowledge of AI and Generative AI to assess the technical consequences of choices.
• Understanding of how technologies such as language models, RAG, agents, and inference become part of a broader technical architecture.
• Ability to clearly substantiate architecture choices for both technical and non-technical stakeholders.
• Independent, responsible, and proactive in collaborating with other disciplines.

Desired.

• Experience or in-depth knowledge of Large Language Models and Generative AI.
• Experience with RAG, embeddings, and vector technology.
• Experience with AI agents and agentic AI.
• Knowledge of model serving, inference, and AI infrastructure.
• Experience with Kubernetes, containers, cloud-native, or hybrid cloud architectures.
• Experience with MLOps, AI platforms, open-source or open-weight models, or digital sovereignty.

Competencies.

• Analytical, conceptually strong, communicatively skilled, collaborative, organizationally sensitive, environmentally aware, and results-oriented.