AI Solutions Architect

Overview

In this role you will define scalable, secure AI architectures and act as the technical authority for AI initiatives across the enterprise. You will translate business needs into production-grade solutions, ensuring modularity, security, and governance. Working within the AI & Data Center of Excellence, you'll steer feasibility, design patterns, and handover to delivery teams for scalable deployment. You will shape patterns and templates to enable enterprise-wide AI adoption while balancing cost and performance.

Responsabilità

• Architectural blueprinting and end-to-end design for Generative AI, ML, and agentic workflows
• Ensure modular, reusable architectures aligned with security and compliance standards
• Recommend optimal technical stacks and scalable patterns across the enterprise
• Evaluate technical feasibility, run rapid prototyping (POCs/MVPs), and define integration points
• Support production-grade deployment with attention to latency, cost-efficiency, and reliability
• Provide technical oversight, architecture reviews, and mentorship to cross-functional teams
• Maintain governance-aligned documentation and AI safety, bias mitigation, and human-in-the-loop patterns
• Stay updated on AI patterns (RAG, fine-tuning, multi-agent systems) and validate new capabilities

Requisiti fondamentali

• Bachelor's or Master's Degree in Computer Science, Data Science, Software Engineering, or related quantitative field
• 5+ years designing end-to-end ML and Generative AI architectures
• Proven experience with feasibility assessments, rapid prototyping, and bridging business and engineering
• Experience with enterprise-scale systems, security standards, and AI governance
• Expertise in AI design patterns (RAG, fine-tuning, agentic workflows) and model evaluation frameworks
• Strong technical leadership, stakeholder management across Security, Data, and Infrastructure
• English professional proficiency; Italian or other European languages a plus
• leadership
• stakeholder management
• collaboration across cross-functional teams
• AI design patterns (RAG, fine-tuning, agentic workflows)
• model evaluation frameworks
• architectural pattern definition