• Build and take ownership of AI-powered features designed to enhance Nutrium's platform. • Apply Generative AI technologies, such as LLMs and RAG architectures, to address practical product challenges. • Continuously monitor, troubleshoot, and fine-tune AI solutions, ensuring a balance between key performance metrics and business requirements. • Establish evaluation strategies and quality metrics (including groundedness, safety, latency, and cost) and work to continuously enhance them. • Partner with Product, Engineering, and dietitians to transform requirements into robust, testable AI solutions. • Create and maintain thorough documentation, lead technical discussions, and drive knowledge-sharing initiatives to elevate team practices.

• Build and ship full-stack AI applications: Create frontend experiences and backend systems that power real AI capabilities, iterating based on performance and user feedback • Own the full lifecycle: Take projects from idea through production deployment, ensuring quality, reliability, and scalability • Build foundational infrastructure: Develop search/retrieval services, tool execution layers (MCP servers), workflows, and intelligent agents • Establish measurement systems: Create feedback loops and performance tracking to continuously improve AI system behavior • Solve complex problems: Debug issues across the stack, identify root causes, and implement robust solutions

• Work with a senior team, own the metrics that matter, and build the evaluation backbone of an AI-native hiring platform. • Design and Own Sourcing Metrics: Turn subjective product feedback into structured, quantitative signals that drive improvement. Partner with product and engineering to define sourcing quality metrics (relevance, match accuracy, diversity). • Build and validate measurement frameworks from scratch; Translate qualitative feedback into SQL-based metrics; Communicate metrics and analytic logic across teams; Own the feedback → metric → business insight loop. • Build LLM Evaluation Systems: Define evaluation matrices and success criteria (hallucination rates, tool accuracy, consistency); Implement evaluation frameworks using Langfuse (or similar tools); Build monitoring, baselines, and continuous improvement processes. • Contribute Technically: Write production Clojure / ClojureScript where needed; Collaborate with senior full-stack engineers; Maintain high code standards and quality.

• Own the end-to-end product direction for Reap’s Platform AI capabilities • Design and drive the technical architecture for AI services • Partner closely with Engineering to translate complex AI system constraints into product requirements • Establish standards for AI-first product development