ruby-labs · Ukraine
Skills: TypeScript, Node.js, Python, Ruby, SQL, Testing
ABOUT US Ruby Labs is a leading tech company that creates and operates innovative consumer products. We offer a diverse range of opportunities across the health, education, and entertainment industries. Our innovative teams are driving the future of consumer-led products, and we're always looking for passionate individuals to join us. Learn more about our story at: https://rubylabs.com/about-us/ ABOUT THE ROLE At Ruby Labs we are looking for an AI Engineer (Strong Middle / Senior level) to own and drive the quality, reliability and evolution of our AI systems in production. This is a high-ownership role. You will be responsible for end-to-end delivery of AI features, production stability of AI systems, and data-driven experimentation using tools like Langfuse and Cloudflare AI gateway for model routing. Increasingly, this includes agentic, tool-using AI systems: defining clean tool contracts (including MCP-based tools) and orchestrating how AI interacts with internal services, search and background pipelines. The stack is TypeScript end to end: Node.js and Hono services on Cloudflare Workers with Durable Objects and Containers, PostgreSQL, OpenSearch. Models from several providers run behind an AI gateway, with prompts, traces and evaluations in Langfuse. KEY RESPONSIBILITIES AI Systems Ownership & Feature Delivery - Take ownership of major AI features and LLM workflows and deliver them to production within agreed timelines. - Own AI output quality, structure and predictability across user-facing AI interactions, with consistent structured output across different LLMs for the same request type. - Integrate and orchestrate multiple LLM providers through an AI gateway, managing model selection, fallback strategies and cost optimisation. - Design and orchestrate tool-using and agentic AI workflows: clean tool contracts (including MCP-based tools), function-calling interfaces and reliable AI-to-system integrations. - Build and maintain multi-step LLM workflows and RAG p…
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