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1 day ago
Requirements and responsibilities
Our client is disrupting the clinical trial recruitment space by automating the creation of digital and physical marketing materials.They have a rapidly built, highly functional frontend prototype generated via low-code tooling (React/Next.js) that successfully validates about 70% of the product vision. As they transition from validation to scale, they need a Full Stack Engineer to lead the migration from a prototype architecture to a production-ready system. This includes refactoring the frontend, designing a robust backend architecture from scratch, and implementing a formal orchestration layer for our LLM and image generation pipelines.Responsibilities:Clean up, refactor, and modularize a rapid-prototype React/Next.js frontend. Design and implement a robust, production-ready backend architecture from scratch.Move direct LLM API calls into a structured orchestration layer. Build and optimize advanced prompt engineering workflows and image generation pipelines (specifically leveraging OpenAI's image generation models/DALL-E).Set up data ingestion workflows to parse clinical study protocols. Prepare and structure internal ad-performance training data for potential LLM fine-tuning.Own the deployment, hosting, and monitoring strategy to transition the app from a fragile prototype to a stable, scalable MVP.Ensure best practices for data handling (Note: the app processes study protocols and marketing data, not patient data/PHI, so full HIPAA/SOC 2 compliance is not required for this phase).Requirements:4+ years of professional full-stack development experience (comfortably operating at a strong Mid to Senior level).Deep expertise in React and Next.js.Experience building production-grade backends (Node.js) and deploying apps to stable cloud environments.Hands-on experience integrating LLMs, managing image generation pipelines, handling API rate limits, and implementing orchestration frameworks (e.g., LangChain, LlamaIndex, or custom structured outputs).A "scrappy but disciplined" engineer who isn't afraid to dig into messy, auto-generated code and systematically refactor it without losing momentum.
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