Product Engineer, Full-Stack ( Front-End )

” Our client is a fully funded AI startup building an end-to-end decision-intelligence platform, delivering quantitative, low-latency judgments on complex political, economic, and military events for customers across finance, national security, and other industries. “ Founded by seasoned leaders with backgrounds at Google, Meta, Client, Cerberus Capital, and US intelligence. “ This is a full-stack engineering role with a front-end focus, requiring production-level knowledge of backend architecture, joining a lean, high-caliber engineering team building at the frontier of AI-powered decision tools.

Roles & Responsibilities “ Architect and deploy front-end systems that integrate LLMOps and proprietary structured data pipelines into real-time AI interactions. “ Manage complex state for conversational and time-series based workflows. “ Help define agentic, multi-task experiences based on complex user requirements. “ Drive product improvements through close collaboration with product and management on user-testing initiatives. “ Develop internal tools for R&D sandbox work and internal product quality monitoring, including dashboards of production deployments. “ Build the core customer product surface where users explore model outputs, understand how a result was reached, interrogate reasoning, and organize and share their work with teammates. “ Build customer-facing model scaffolding, the surface where users pose questions to the models and work with results in close integration with proprietary workflows. “ Build internal tooling for research and product quality, including dashboards and comparison tooling for the research team to evaluate model changes, plus quality monitoring for production deployments.

” 3-5 years of experience building production web applications, with proven independent experience in React, TypeScript, and modern front-end frameworks. “ Experience with state management libraries, real-time streaming data handling, and responsive design principles. “ Backend experience with Node.js, Python, and FastAPI. “ Production experience with LLMOps, vector databases, and RAG architectures. “ Strongly preferred: AI-native experience shipping LLM-facing product surfaces in production, including streaming chat, agentic/multi-step tool use, citation and grounding UI, and human review/feedback loops. “ Strongly preferred: comfort with quantitative and probabilistic concepts, including calibration, scoring rules (Brier/log score), backtesting, and confidence intervals. “ Strongly preferred: experience on venture-backed startup teams, comfortable with the ambiguity and scope of an early product surface. “ Strongly preferred: design-system fluency (Tailwind, Radix, shadcn/ui, Figma-to-code workflows) and genuine care about visual craft. “ Strongly preferred: prior work on tools for financial, intelligence, or research users, surfaces where being wrong is expensive and provenance is not optional.

” Compensation: competitive salary plus equity package.