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 a Senior AI Engineer 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 major AI features , production stability of AI systems, and data-driven experimentation using tools like Langfuse, Mixpanel and OpenRouter . You’ll work in a modern stack built on Next.js, TypeScript, Node.js, and Redis , collaborating closely with product, growth, data, and billing teams. Increasingly, this includes building agentic, tool-using AI systems — defining clean tool contracts (including MCP -based tools) and orchestrating how AI interacts with internal services and business systems.
Our engineering organization uses a squad-based structure. You will operate within an AI engineering squad, contributing as a senior technical voice and driving engineering quality within your area of the product. Key Responsibilities AI Systems Ownership & Feature Delivery • Take complete ownership and deliver major AI engineering features within agreed timelines • Own AI output quality, structure, and predictability across all user-facing AI interactions • Design, implement, and maintain output-type–based AI systems, including segmentation, routing, and enforcement • Ensure consistent output structure and formatting across different LLMs for the same request type • Integrate and orchestrate multiple LLM providers via OpenRouter, managing model selection, fallback strategies, and cost optimisations • Design and orchestrate tool-using / agentic AI workflows — defining clean tool contracts (including MCP-based tools), function-calling interfaces, and reliable AI-to-system integrations • Build and maintain complex, multi-step LLM workflows — including with orchestration frameworks such as LangChain or LlamaIndex — for advanced reasoning, context reuse, and retrieval Prompt Engineering & Experimentation • Design and manage production prompt systems with dynamic prompting, context injection, and conditional logic • Own the deployment and release of LLM experiments, prompt management, and Langfuse-based evaluation pipelines • Run A/B tests across models, analyse results, and present data-driven impact assessments of AI features and experiments • Monitor AI system metrics, quality signals, latency, and release health using Langfuse and other observability tools • Deep-debug complex LLM chains using Langfuse traces — identifying bottlenecks and optimising for cost, latency, and context-window usage — and build output-scoring to root-cause hallucinations and logic errors Code Quality & Production Reliability • Write clean, scalable, and maintainable TypeScript code across the Next.js / Node.js stack • Build reliable backend logic for AI systems, with strong error handling, request validation, fallback flows, and predictable behavior in production — including reliable tool execution and AI-to-service integrations • Ensure high code quality through testing, code reviews, and clear engineering standards • Monitor, troubleshoot, and improve production performance, reliability, and system health • Drive maintainability and technical quality through solid architecture, refactoring, and disciplined release practices Qualifications 6+ years of backend/full-stack software engineering experience, including production-grade TypeScript/Node.js .
Experience with Next.js and/or Python is a plus. 2+ years of experience building AI/LLM systems in production. Less experience may be considered for exceptional candida