Michael Hagar

Led full-stack development for a fintech market intelligence platform used to analyze trading activity, pricing behavior, liquidity trends, and other real-time signals for financial teams. Architected the frontend across the product using React, TypeScript, Next.js, and Storybook, establishing a reusable design system with tokens and theming and ensuring WCAG 2.2 accessibility. Built high-performance data visualizations and workflows for search, monitoring, and analysis; improved LCP and TTI via edge rendering, ISR, prefetching, and caching. Collaborated with FastAPI and Node.js services to implement validation layers, integrations, and policy-aware response handling. Created an AI agent experience with multi-turn interactions, tool traces, response comparisons, and guard rails. Delivered observability and evaluation dashboards for LLM behavior, and supported product, ops, and review teams with internal platforms to evaluate model behavior and safety.

Led frontend and data tooling for a fintech platform at scale, using React, TypeScript, Next.js, and Storybook to deliver robust UI components and a design system. Built real-time dashboards and analytics for market data; implemented edge rendering and caching to improve LCP/TTI. Partnered with backend teams on API integrations (Node.js, FastAPI) and validation layers to enable reliable data workflows. Drove AI-assisted flows with multi-turn interactions and guard rails; built observability dashboards to monitor model behavior and user interactions. Advocated for accessibility and testing processes across teams.

Built large-scale, highly interactive data grids and visualization components with virtualization and progressive loading for analytics across multi-terabyte datasets. Implemented self-service product flows for exports, webhooks, saved views, and alert configurations; established data access controls and testing harness. Drove backend integration with Node.js and Python services; connected to Snowflake, PostgreSQL, Redis, and other data stores; and supported reliable delivery of analytics features.