Azure Observability Engineer (Build & Implementation)

Remote position within Argentina & Uruguay RYZ Labs is seeking a highly skilled and experienced Full Stack AI Engineer to join our client’s team, focused on building and implementing enterprise-grade monitoring solutions across Azure environments. You’ll work across frontend, backend, cloud, and AI-enabled systems, collaborating closely with product, engineering, and cross-functional teams to develop scalable solutions, improve system reliability, and deliver high-quality user experiences. Basic Qualifications: 5–8 years of experience as a Full Stack Engineer or Software Engineer Strong proficiency in two or more of the following: JavaScript/TypeScript, Python, or C#/.NET Experience building modern web applications using frameworks such as React, Next.js, Vue, or Angular Strong experience designing and consuming REST APIs and working with microservices architectures Hands-on experience using AI coding tools such as Claude Code, Cursor, GitHub Copilot, or similar tools in professional workflows Experience working with Azure cloud platform Experience with containerization tools such as Docker and CI/CD pipelines Strong understanding of software development best practices, testing, scalability, and system reliability Experience working in Agile development environments Strong communication and collaboration skills Key Responsibilities: Develop and maintain full stack applications and services using modern frontend frameworks and backend technologies Design, build, and deliver scalable, high-performance features and systems across web applications and distributed architectures Leverage AI coding tools such as Claude Code, Cursor, and GitHub Copilot to accelerate development workflows and improve code quality Review and validate AI-generated code for correctness, security, performance, and maintainability Build and improve AI-assisted engineering workflows for automation, testing, documentation, and development efficiency Contribute to modernizing legacy services and architectures using cloud-native design patterns Design and consume REST APIs and support microservices-based systems Collaborate with product, engineering, design, and security teams to deliver resilient and customer-focused solutions Support cloud infrastructure, distributed systems, and backend reliability initiatives Contribute to improving scalability, observability, performance, and operational efficiency Help safeguard privacy, security, and data protection across implementations Mentor junior engineers and contribute to technical discussions, architecture decisions, and engineering best practices Nice to Have: Experience with AI development workflows, prompt engineering, or AI-assisted coding practices Familiarity with Model Context Protocol (MCP) and AI agent integrations Experience mentoring engineers and contributing to architectural decisions Interest in emerging AI development tools and intelligent engineering workflows Originally posted on Himalayas