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