Full Stack AI Engineer (.NET)
RYZ Labs is looking for a Full Stack AI Engineer to help build and improve intelligent features across our client’s platform. This role involves working across both frontend and backend systems, with a focus on integrating AI capabilities into user-facing and internal tools.
You’ll collaborate with product, engineering, and data teams to develop scalable solutions that enhance user experience, automate workflows, and improve system efficiency.
About RYZ Labs:
RYZ Labs is a startup studio founded in 2021 by two lifelong entrepreneurs. Our teams are remote and distributed across the US and LatAm, working with cutting-edge technologies to build scalable, impactful products.
At RYZ, you’ll work with autonomy and ownership in a fast-paced environment, contributing to meaningful projects while continuing to grow alongside a strong team.
Responsibilities:
Develop and maintain full stack applications using modern frontend frameworks (React or similar) and .NET-based backend services
Build and integrate AI-powered features (e.g., automation, summarization, recommendations) into existing workflows
Design and consume REST APIs and support backend services in .NET
Collaborate with cross-functional teams to identify opportunities for automation and AI-driven improvements
Work with structured and unstructured data to support AI/ML use cases
Contribute to improving system performance, scalability, and reliability
Support basic monitoring and troubleshooting of production systems
Basic Qualifications:
3–5+ years of experience as a Full Stack Engineer or Software Engineer
Strong experience with .NET (C#) for backend development
Experience with JavaScript/TypeScript and a modern frontend framework (React preferred)
Familiarity with building and consuming REST APIs
Basic experience working with AI/ML concepts or tools (e.g., APIs, LLMs, or automation workflows)
Experience working with cloud platforms (AWS, Azure, or GCP) is a plus
Good understanding of software development best practices
Nice to Have:
Exposure to AI tools such as OpenAI, embeddings, or prompt-based systems
Experience with SQL or NoSQL databases
Familiarity with CI/CD pipelines
Interest in automation and improving operational workflows
