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Tech Stack
About the role
- 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.
Benefits
- 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.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Prompt EngineeringDynamic PromptingNode.jsNext.jsOpenRouterLangfuseEvaluation MethodologyModel PerformanceFine-TuningData Analysis
Soft Skills
Analytical MindsetIterative Mindset