AI Engineer

Ruby Labs

. 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.

Posted 4/21/2026full-timeRemote • 🇪🇸 SpainMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

JavaScriptNext.jsNode.js

About the role

Key responsibilities & impact

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

What you’ll need

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.

Benefits

Comp & perks

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.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Prompt EngineeringDynamic PromptingNode.jsNext.jsOpenRouterLangfuseEvaluation MethodologyModel PerformanceFine-TuningData Analysis

Soft Skills

Analytical MindsetIterative Mindset