AI Engineer

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’re seeking a senior AI Engineer (Node.js / Next.js / TypeScript) to shape our AI infrastructure and drive production-ready LLM experiences. You’ll work in a modern stack, making data-driven decisions around model performance, reliability, and cost. You’ll own advanced prompt systems, structured outputs, and complex LLM workflows using LangChain or LlamaIndex. Observability, debugging, and evaluation are core to the role, leveraging Langfuse and AI gateways like OpenRouter to continuously improve model quality and operational efficiency. You’ll take full ownership of key AI features from experimentation to live production. #### Key Responsibilities - Advanced Prompt Engineering: Designing complex, dynamic prompt templates with conditional logic and efficiently reusing information and context within prompts to maximize generation quality and reasoning. - Structured Outputs & Schemas: Implementing various response schemes (JSON mode, function calling, Zod/JSON schemas) to ensure AI outputs are predictable and ready for seamless integration into application logic. - Prompt Engineering & Evaluations: Building robust evaluation pipelines and using Langfuse to collect feedback and score the quality of responses in real time. - Tracing & Debugging: Performing deep debugging of complex LLM chains using Langfuse traces to identify bottlenecks and optimize for cost, latency, and context window usage. - AI A/B Testing: Running systematic experiments across different models via OpenRouter (e.g., comparing Claude 3.5 Sonnet vs. GPT-4o) and analyzing results based on quantitative metrics. - Data-Driven Decisions: Making deployment decisions for new prompts or models strictly based on quantitative benchmarks and trace data, rather than intuition. - Output Scoring & Analysis: Developing scoring systems to analyze the “Problem → Solution” chain and identify root causes of hallucinations or logic errors using Langfuse analytics. - Model Performance & Fine-Tuning: Regularly re-evaluating model performance as new architectures emerge and performing fine-tuning when necessary to meet specific domain requirements. #### Location Ruby Labs operates within the CET (Central European Time) zone. Applicants from any country are welcome to apply for the position as long as they are located within approximately ± 4 hours of CET. This ensures optimal collaboration and communication during working hours. #### Life at Ruby Labs At Ruby Labs, we move fast, aim high, and expect the same from our team. We’re not here to play small—we’re here to build, grow, and win. That means we look for people who are ambitious, driven, and ready to give their best every single day. This is a place for individuals who thrive under pressure, embrace challenges, and see opportunity in every obstacle. If you’re hungry to achieve, motivated by impact, and want to grow at the speed of your own ambition, Ruby Labs offers the platform to make it happen. Here, effort is matched with reward. We recognize those who go all in and deliver results, and we create space for people who want more—more responsibility, more growth, and more success. #LI-Remote