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At RubyLabs, 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.
Job Responsibility:
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
Requirements:
Node.js & Next.js: Deep knowledge of the stack to build reliable services and handle complex LLM-generated data
Dynamic Prompting Skills: Proven experience in building prompts where content is highly dependent on input variables and context injection
OpenRouter Experience: Experience working with unified APIs, managing rate limits, and selecting the most cost-effective models for specific tasks
Langfuse (or similar): Understanding of LLM observability principles — setting up tracing, creating test datasets, and integrating scoring systems
Evaluation Methodology: Experience with frameworks like RAGAS or building custom “LLM-as-a-judge” systems
Analytical Mindset: Ability to transform raw generation logs into actionable business metrics and technical insights
Iterative Mindset: Focus on continuous product improvement through constant feedback loops
Nice to have:
Fine-Tuning: Practical experience in fine-tuning models for specific domain tasks or JSON compliance
RAG Architecture: Understanding how to build and optimize Retrieval-Augmented Generation systems, including indexing, retrieval, and re-ranking
Python: Basic knowledge for working with data science scripts or AI evaluation libraries
What we offer:
Remote Work Environment: Embrace the freedom to work from anywhere, anytime, promoting a healthy work-life balance
Unlimited PTO: Enjoy unlimited paid time off to recharge and prioritize your well-being, without counting days
Paid National Holidays: Celebrate and relax on national holidays with paid time off to unwind and recharge
Company-provided MacBook: Experience seamless productivity with top-notch Apple MacBooks provided to all employees who need them
Flexible Independent Contractor Agreement: Unlock the benefits of flexibility, autonomy, and entrepreneurial opportunities. Benefit from tax advantages, networking opportunities, reduced employment obligations, and the freedom to work from anywhere