Cloud & AI Platform Architect
Pubblicato il 18-09-2026 - Crif in Roma
AI Platform Architect
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Role Overview The
AI Platform Architect
is responsible for designing and leading the evolution of enterprise AI platforms, enabling the delivery of scalable, secure, and production-ready AI solutions across multiple business domains. The role focuses on Generative AI technologies, including RAG, Agentic AI, Multi-Agent Systems, and MCP-based architectures, leveraging platforms such as AWS Bedrock, Azure AI Foundry, and other emerging AI ecosystems. The architect defines reference architectures, governance standards, observability practices, and operational frameworks, while continuously exploring new technologies and transforming innovative AI concepts into enterprise-grade capabilities.
Key Responsibilities Lead the design and industrialization of Generative AI and Agentic AI solutions from prototype to production. Deliver enterprise-scale RAG, Agentic, Multi-Agent, and MCP-based architectures. Explore, evaluate, and integrate emerging AI technologies, frameworks, and foundation models into the enterprise AI ecosystem. Build reusable AI patterns, accelerators, and platform capabilities that enable rapid adoption across multiple business domains. Define standards for AI engineering, observability, evaluation, governance, security, and reliability. Work closely with data, software, cloud, and business teams to transform AI use cases into production services. Drive continuous experimentation and innovation while maintaining enterprise-grade quality, security,
and compliance standards. Mentor teams and promote best practices around modern AI architectures, cloud-native platforms, and operational AI.
Required Skills Proven experience designing and delivering
AI-based solutions in production environments . Hands-on experience with
Generative AI platforms
such as
Azure AI Foundry ,
AWS Bedrock , or equivalent AI ecosystems. Strong experience implementing and operating
RAG (Retrieval-Augmented Generation)
architectures in enterprise contexts. Experience designing and deploying
Agentic AI systems , including orchestration patterns, tool usage, and multi-agent workflows. Knowledge and practical adoption of
Model Context Protocol (MCP)
or equivalent agent integration patterns. Experience with cloud-native architectures on
AWS
and/or
Azure . Strong understanding of platform reliability, security, scalability, and operational excellence.
Preferred Skills Kubernetes (K8s) Terraform Python CI/CD and DevOps practices AI Observability and monitoring solutions LLMOps and AI platform operations Responsible AI, AI Governance,
and AI Risk Management Knowledge of the EU AI Act and related regulatory frameworks Experience with evaluation frameworks for LLMs, agents, and GenAI applications Vector databases, semantic search, and knowledge retrieval platforms
Success Measures Delivery of enterprise-scale AI solutions that successfully reach production. Adoption of AI capabilities across multiple business domains and markets. Secure, scalable, observable, and compliant AI platforms and architectures. Creation of reusable AI assets, patterns, and accelerators that increase delivery speed. Continuous innovation through the evaluation and adoption of emerging AI technologies. Strong governance and Responsible AI practices embedded across the AI lifecycle.
We offer a safe and inclusive environment where colleagues are encouraged to think outside the box. CRIF is committed to creating a diverse, inclusive work environment and promoting equal opportunities throughout the employee life cycle. We aim to attract and retain the best people and embracing gender, age, culture, religion and disability diversity What we offer: Type of contract: permanent The Annual Salary for this position starts from €37,000 gross per year. xpavfwm The level of classification will be determined during the selection process based on the candidate’s profile and in accordance with the National Collective Labour Agreement (CCNL) for the Tertiary, Distribution and Services sector. The final compensation package, including any variable components (such as MBO) or additional benefits