Expert AI Architect – LLM & GenAI Integration

Editx; Brussel; On-site; EUR 90,000 - 130,000; Full time

Job summary

Editx in Brussels is seeking a pioneering Enterprise Architect to shape generative AI and ML target architectures across on-premises, cloud and hybrid environments. You will define frameworks and decision patterns, guiding teams from PoC to production while embedding privacy, least privilege, and data minimization by design in collaboration with security teams.

You will also prioritize reusable platform components for the internal development platform.

Qualifications

• Develop and maintain the target architecture for generative AI, ML, and agentic AI.
• Establish reference architectures for on-prem, cloud, and hybrid deployments.
• Define architectural frameworks for AI Gateways, Model Context Protocols, retrieval, and model access.
• Guide delivery teams through architectural choices and transitions from proof-of-concept to production.
• Integrate privacy, least privilege, and data minimization principles by design in collaboration with security teams.
• Identify and prioritize reusable platform and integration building blocks for the internal development platform.

Responsibilities

• Develop and maintain the target architecture for generative AI, ML, and agentic AI.
• Establish reference architectures for on-prem, cloud, and hybrid deployments.
• Define architectural frameworks for AI Gateways, Model Context Protocols, retrieval, and model access.
• Guide delivery teams through architectural choices and transitions from proof-of-concept to production.
• Integrate privacy, least privilege, and data minimization principles by design in collaboration with security teams.
• Identify and prioritize reusable platform and integration building blocks for the internal development platform.

Job description

Responsibilities

• Develop and maintain the target architecture for generative AI, machine learning, and agentic AI.
• Establish reference architectures and decision patterns for on-premises, cloud, and hybrid deployments.
• Define architectural frameworks for AI Gateways, Model Context Protocols, retrieval, and model access.
• Guide delivery teams through architectural choices and transitions from proof-of-concept to production.
• Integrate privacy, least privilege, and data minimization principles by design in collaboration with security teams.
• Identify and prioritize reusable platform and integration building blocks for the internal development platform.