AI Domain Architect Position

Start Date: ASAP

Duration: 1 year

Location: Brussels

Work Regime: Full-time

Application Deadline: 12/09

Description:

As an AI Architect within our Agile organization, you will play a pivotal role in designing and implementing scalable, intelligent solutions. You will collaborate across multidisciplinary teams, including developers, analysts, business stakeholders, and architects, to ensure seamless integration of AI capabilities into the enterprise ecosystem. You will work within the Agile model, leveraging MVP principles and iterative delivery to maximize business value and minimize time-to-market.

Key Responsibilities:

• AI Interaction Solutions: Architect and support the implementation of textbots and voicebots across mobile and web platforms.
• Enterprise Integration: Connect conversational agents with domain architecture (payments, billing, case management, etc.) using scalable APIs.
• Advanced Retrieval Systems: Design sophisticated RAG-based knowledge systems (e.g., metadata RAG, agentic RAG, graphRAG, multi-source RAG).
• Data Pipelines: Build automated and scalable data processing workflows.
• Monitoring & Reporting: Develop automated business monitoring and reporting solutions.
• Documentation: Use LeanIX, C4 models, and Visio for architectural documentation.
• Agile Delivery: Manage agile design to delivery with bi-weekly sprints, operating across Squads and Tribes.
• Strategic Advisory: Provide expert content and guidance on AI solutions and cost-benefit optimized implementation strategies.
• Cross-functional Collaboration: Work effectively with developers, analysts, architects, and business stakeholders.
• Innovation Leadership: Promote awareness of emerging AI trends, technologies, and solutions across the organization.

Skills and Qualifications:

• Excellent communication and presentation skills, with the ability to simplify complex concepts around (Gen)AI.
• Ability to analyze, evaluate, and visually represent (Gen)AI results, with knowledge of different measurements and KPIs.
• Proven ability to design and orchestrate agentic AI systems using frameworks, enabling autonomous multi-agent collaboration for task execution and decision-making.
• Experience in architecting GenAI solutions for customer-facing applications.
• Hands-on experience with multimodal LLMs/SLMs tools like OpenAI, CrewAI, LangChain, LangGraph, Azure Vector Search, AWS Kendra.
• Deep understanding of RAG-based architectures and their applications.
• Experience building solutions on Azure or AWS, aligned with a buy-over-build strategy.
• Experience with event-driven systems like Kafka and similar data ingestion tools.
• Proficiency with data tools such as Dataiku and Databricks for data processing.
• Strong experience integrating enterprise platforms.
• Familiarity with monitoring and reporting tools like Elastic, Kibana, and PowerBI for automated insights and reporting.
• Experience with agile methodology and way-of-working.