AI & Data Architect
Listed on 2025-12-20
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IT/Tech
AI Engineer
Are you the AI & Data Architect who inspires and guides clients through their AI and data-driven transformation? As a client-facing AI & Data Architect at iO, you are the strategic sparring partner who helps organisations discover, shape and realise their AI and data opportunities.
In this role, you are the bridge between cutting-edge AI technology and business strategy. You work closely with customers and prospects to identify their (business) issues, translate these into concrete AI and data solutions, and work hands-on on solutioning and developing POCs. You are the one who makes complex AI concepts accessible and gets customers excited about the possibilities.
You combine strategic insight with hands-on AI and data expertise. From analysing customer challenges to co-developing Large Language Model implementations, RAG patterns and data architectures. You work with lead developers on concrete solutions and are the person who then presents these convincingly to customers and stakeholders.
You will mainly be involved in commercial projects and the discover & define phases, where you will use your AI and data expertise commercially to inspire customers and design concrete solutions.
What are your responsibilities as an AI & Data Architect?- Client-facing solutioning:
Working with clients and prospects to identify business issues and translate them into concrete AI and data solutions - Commercial involvement:
Contributing AI and data expertise to sales processes, devising solutions and estimating the workload for complex AI projects - Hands-on development:
Collaborate with lead developers on solutioning and develop POCs to make concepts tangible. - Client presentations:
Explain AI solutions and architectures to clients, explain complex technology in an accessible way and act as a sparring partner. - AI & Data architecture:
Design scalable AI solutions, data pipelines and integration of LLMs, RAG patterns and analytics platforms. - Trend watching:
Following the latest AI and data developments and translating them into practical opportunities for customers - Knowledge sharing:
Supporting AI awareness and capabilities in the organisation through internal sessions and knowledge sharing - Thought leadership:
Using your knowledge commercially through blog posts, customer inspiration sessions and external speaking engagements - Discover & Define support:
Contributing ideas during project phases about the right architectural choices and approach, after which you hand over to development teams
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