Design and lead cloud architectures on Azure, covering networking, security, governance, IaaS, PaaS and serverless solutions.
Own the infrastructure of AI-powered platforms, including conversational AI systems with: Retrieval-Augmented Generation (RAG), Document ingestion, processing and vector search and Integration with LLM providers and AI services.
Build and evolve CI/CD pipelines for both application and infrastructure, following DevSecOps best practices.
Develop Infrastructure as Code (Terraform) with a strong focus on reusability, scalability and maintainability.
Design and operate production-grade environments, ensuring: High availability and performance, monitoring, logging and observability and cost optimization and reliability.
Collaborate closely with AI, data and software teams to productionize ML/LLM solutions (MLOps mindset). Actively propose improvements and new technical approaches, contributing to architectural decisions and technical roadmaps.
Work in Agile, autonomous, multidisciplinary teams, with real ownership from design to production.
Requirements
Strong experience with Microsoft Azure in real production environments.
5+ years of hands-on experience in Cloud / DevOps / Platform Engineering roles.
Proven experience designing and implementing IaaS, PaaS and cloud-native architectures.
Solid knowledge of networking, security and governance models in cloud environments.
Experience with Azure DevOps (Repos, Pipelines) and CI/CD practices.
Strong background in Infrastructure as Code (Terraform).
Experience monitoring and operating high-traffic, production web platforms.
Familiarity with AI/ML or LLM-based platforms in production environments.
Comfortable working with Agile methodologies, Jira and Confluence.
Fluent English (mandatory) — you’ll work daily with international teams and clients.
Very nice to have:
Experience in hybrid and multi-cloud environments (AWS / GCP).