Data & AI Architect

About the role

The Data & AI Architect will design, lead and evolve the organization’s data and artificial intelligence architecture. The role ensures that advanced analytics and generative AI solutions are scalable, secure, ethical and aligned with business strategy, providing a robust data infrastructure for decision‑making.

Key responsibilities

• Define canonical data schemas and models to enable strategic analysis and link data quality to AI/ML accuracy.
• Design end‑to‑end pipelines that integrate DataOps with LLMOps, supporting continuous data ingestion, model inference and retraining.
• Build and evolve Lakehouse/Data Mesh ecosystems optimized for Generative AI and advanced analytics workloads.
• Implement security layers, guardrails and data‑quality, lineage and compliance policies (GDPR, AI Act, NIST AI RMF) for AI models.
• Develop Retrieval‑Augmented Generation (RAG) architectures that combine structured (SQL) and unstructured (NoSQL/Document) sources with vector databases.
• Design frameworks for single‑ and multi‑agent AI solutions and event‑driven enterprise applications.
• Evaluate and select ML/LLM/SLM models (open‑source or proprietary) based on cost and latency to optimize performance for each use case.

Required profile

• Degree in Engineering, Computer Science, Statistics, Mathematics or a related field.
• Preferably a postgraduate degree or master’s in Machine Learning, AI or a comparable discipline (not mandatory).

Required skills

• Data modeling and schema design
• Data pipelines (DataOps, LLMOps)
• Lakehouse and Data Mesh architecture
• Generative AI (GenAI) concepts
• Retrieval‑Augmented Generation (RAG)
• SQL and NoSQL/Document databases
• Vector database technologies
• Machine Learning and Large Language Model deployment
• Model evaluation focusing on cost and latency
• Knowledge of GDPR, AI Act and NIST AI RMF compliance