Vetted Vue.js Professionals

“Frontend engineer with end-to-end ownership of React/Next.js products, focused on scalable component-based architecture and quality via CI/CD, automated testing, and disciplined PR reviews. Built React + TypeScript dashboards with role-based views using Zustand, and improved existing codebases by decoupling components and boosting performance through code splitting, lazy loading, and standardized shared components.”

“Built and shipped a production "Campaign AI" multi-agent system (LangGraph) that personalizes B2B outbound emails at scale using Apollo.io prospect data, clustering-based segmentation, and 21 persona variants. Notably uncovered that high click rates were largely email security scanners and created a validated bot-detection/scoring pipeline (timestamps/IP/user-agent/click patterns), bringing reported engagement down from ~40% to a trusted 5–8% that aligned with real conversions.”

“Built and shipped an AI-powered journaling app feature that analyzes user text for emotions in real time, owning everything from React/TypeScript UX (dynamic theming + Framer Motion) to a FastAPI backend integrating Hugging Face. Has hands-on production experience deploying Dockerized services on AWS (EC2/RDS/S3/CloudWatch) with GitHub Actions CI/CD, and resolved a real latency/scaling incident by converting blocking external API calls to async with retries/timeouts.”

“Hands-on technical/product-facing engineer with experience operationalizing LLM/agentic workflows and debugging them in real time using logs, traces, and metrics. Also supports go-to-market by running developer-focused live coding demos and partnering with sales on discovery and integration/maintainability concerns through clear technical documentation.”

“Frontend-focused developer who built a chess web product end-to-end (including an admin panel) using Next.js with SSR. Emphasizes reusable component architecture, performance optimization (bundle-size reduction, lazy loading), and quality practices like Lighthouse audits and Playwright E2E testing, with hands-on experience handling Next.js hydration pitfalls.”

“Built and owned end-to-end systems for the Department of Water Resources and NAHC, including a debt infrastructure management system and a TypeScript/React + .NET 6 CMS. Strong in shipping quickly with quality (CI/CD, automated testing), optimizing SQL Server performance for large datasets, and implementing microservices-style async processing with reliability patterns (retries/idempotency/monitoring). Also delivered widely adopted internal workflow automation and reporting using Power Automate and Power BI.”

“Frontend lead on a campaign management platform, owning architecture and delivery in Next.js (App Router) with TypeScript types derived from Swagger contracts and Zustand state management. Built and shipped complex, form-heavy multi-step flows like QR code creation with live preview/analytics considerations, and improved maintainability by extracting shared table/filter abstractions while proactively defining UX edge states with design.”

“Frontend-focused engineer who has led complex React/TypeScript analytics dashboards end-to-end, including a Next.js internal customer dashboard scaled to thousands of daily users. Emphasizes scalable architecture (feature-based structure, typed models, React Query/Zustand), strong quality gates (Jest/RTL, linting, monitoring with Sentry/LogRocket), and performance optimization, with tight collaboration with design/product via Figma and rapid prototyping.”

“Full-stack engineer with experience delivering an end-to-end NIH application using Angular and scalable .NET Core microservices backed by MySQL. Has hands-on depth in complex approval/workflow implementations (RBAC + workflow engine) and performance tuning for million-record, data-driven systems, plus 5 years with Java/Spring Boot microservices and React.”

“Frontend engineer (~4 years) who led an admin dashboard for potato farmers end-to-end, integrating real-time and historical weather data to drive disease-severity predictions. Built scientifically validated calculation pipelines (FAO Penman-Monteith, late blight models), rigorous Cypress/unit testing, and print/PDF-ready reporting, while optimizing performance and API load with debouncing, caching, and feature-flagged rollouts.”