Aws Architect/ Solution Architect Remote
Pubblicato il 18-10-2026 - Msx International in Roma
Overview In this role you willDesign scalable, secure AI architectures and production-grade pipelines. Serve as the primary technical authority within the AI & Data Center of Excellence, translating business requirements into robust engineering solutions. You will guide feasibility assessments, prototype fast, and ensure modular, governance-aligned designs for enterprise deployment.
You'll collaborate across Security, Data, and Infrastructure to enable scalable AI initiatives with measurable impact.
Responsabilità Architectural blueprinting and reference architecture recommendations for AI solutions Design end-to-end pipelines for Generative AI, ML, and agentic workflows Ensure modularity, reuse, security, and compliance in AI architectures Recommend optimal technical stacks for business use cases Collaborate with AI governance to align with risk and lifecycle requirements Conduct feasibility assessments, rapid prototyping (POCs/MVPs), and define technical requirements Provide high-level effort estimations and resource needs Define scalable production requirements and latency/cost/reliability targets Establish AI safety, bias mitigation,
and human-in-the-loop patterns Provide technical oversight and architecture reviews for AI projects Stay up-to-date with AI patterns (RAG, fine-tuning, multi-agent systems) and validate models and tools Maintain concise architectural documentation for governance and auditability Requisiti fondamentali ~5+ years designing end-to-end architectures for ML and Generative AI ~ Experience with feasibility assessments, POCs/MVPs, and business-engineering alignment ~ Experience with enterprise-scale systems, security standards, and AI governance ~ Proven ability to lead technical initiatives and mentor teams ~ Strong stakeholder management across Security, Data, and Infrastructure ~ Solid knowledge of ML design patterns and model evaluation frameworks ~ Strong leadership and mentorship ~ Stakeholder management ~ Cross-functional collaboration ~ AI design patterns (RAG, Fine-tuning, Agentic workflows) ~ Model evaluation frameworks ~ Architectural pattern design for modular AI systems