Vetted REST APIs Professionals

Umair Shamoon

Screened

Mid-level Full-Stack Developer specializing in MERN/MEAN and cloud-native web apps

8y exp

“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.”

“Full-stack product engineer who has shipped AI-powered job board moderation and validation features end to end across React/TypeScript, serverless backends, and Postgres. Stands out for combining UX polish, LLM-backed workflow design, and reusable async infrastructure patterns to improve reliability, speed of delivery, and user participation.”

“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.”

Akash Parekh

Screened

Mid-level Full-Stack Developer specializing in React, Node.js, and cloud deployment

Toronto, Canada3y exp

“Frontend engineer with experience building enterprise ERP/CRM dashboards in React + TypeScript, including cron-driven data updates and differentiated state flows. Emphasizes CI/CD pipeline setup, performance optimization (Core Web Vitals, React Profiler), and disciplined delivery practices (risk-based QA, phased rollouts); also has Figma-to-responsive implementation experience.”

Bay Sukh

Screened

Mid-level Full-Stack Developer specializing in Java/Spring and modern web SPAs

Remote6y exp

“Full-stack Java/Spring Boot + SPA (Angular/React) engineer who has delivered products end-to-end, including a financial management portal for SMBs and a high-traffic golf/hotel reservation platform. Notably migrated a manually deployed system to AWS (EC2/RDS/S3/CloudFront) with Jenkins CI/CD and has hands-on React performance optimization experience for LG webOS TV apps.”

“Built production-style backend and AI systems across internship and project work, including a real-time sports platform backend and a Smart Email Assistant using GPT-4. Stands out for combining classic backend performance engineering with practical LLM workflow design, including measurable latency improvements, high uptime, and debugging of non-deterministic model behavior.”

Naseem Khan

Screened

Junior Full-Stack Developer specializing in React/Next.js and Node.js

Islamabad, Pakistan2y exp

“Frontend engineer who led the Cariveco frontend end-to-end, establishing a scalable React/TypeScript architecture with a design system, CI-driven quality gates, and strong performance practices (Lighthouse, code-splitting, caching). Experienced building complex dashboards with role-based views and real-time data using Redux + RTK Query, and shipping major features quickly with automated testing, feature flags, and Sentry monitoring.”

Amr Ibrahim

Screened

Mid-Level Front-End React Developer specializing in dashboards and real-time web apps

Maadi, Cairo, Egypt6y exp

“Frontend engineer who helped build a desktop-as-a-service product from scratch and has delivered complex React + TypeScript workflows (including multi-stage approvals). Notable for performance-focused refactoring (removing unnecessary memoization), building reusable component patterns, and leading a major shift from hard-coded forms to a configurable form-builder with strong dev/QA collaboration and heavy scenario testing.”

Toufiq Hasan

Screened

Entry-level Software Engineer specializing in backend and AI integration

New York, NY1y exp

“Built and shipped an LLM-powered crypto price tracking and alert agent in a web environment that scaled to roughly 10,000 users. The candidate emphasizes production reliability, structured outputs, and data normalization, and cites strong product impact including retention growth from 35% to 65% and roughly 95% positive user validation on alert interpretations.”

“Early-career backend developer building an Arc Raiders game-data API end-to-end in Go on AWS with PostgreSQL, making their first real deployment and learning system design hands-on. Also built an AI resume and cover letter generator using Gemini and has experience debugging open-source code and managing PRs in a capstone team project.”

“Backend-focused full-stack engineer with strong React/TypeScript depth who has owned end-to-end features spanning PostgreSQL, .NET 8 APIs, real-time React dashboards, and production monitoring. Notably built a geofencing tracking module for construction SaaS and a 0→1 secure LAN file transfer engine, combining security-first architecture with measurable outcomes like 40% lower battery usage and zero security breaches in pilot.”

“Full-stack developer who has led end-to-end delivery of web applications using React/TypeScript with Node/Express and SQL databases. Notably modernized a legacy Java applet ERP system by redesigning it in React, iterating based on user feedback to balance new UX improvements with existing user workflows.”

“Early engineering hire at The Coaching Market (B2B2C e-learning startup) who owned re-engineering core REST APIs (FastAPI) and shipping an enhanced Next.js UI, plus automating most deployments via CircleCI/Vercel. Strong in data-driven iteration (surveys/Jira/Slack + Google Analytics, A/B tests) and reliability/performance improvements with measurable impact (30% less downtime, 40% faster releases, 25% faster loads).”

“Backend/ML engineer with deep fintech and marketplace experience: built a real-time financial analytics + algorithmic trading platform (Python/Postgres/Kafka/Redis) and drove major DB performance wins (10x faster analytics; sub-10ms response consistency). Also shipped an end-to-end ML recruitment matching platform (scraping/ETL/modeling/Django deployment) with reported 92% matching accuracy, and emphasizes production reliability via monitoring, blue-green deploys, and robust workflow error handling.”

“Built and shipped a production LLM-powered document processing agent (ingestion→OCR→LLM extraction/classification→validation→DB/workflow triggers) using Kafka and PostgreSQL. Emphasizes production reliability with strict JSON schemas, idempotent services, retries/backoff, fallback models, and human-in-the-loop review—driving ~90% automation, minutes-to-seconds processing, and ~10x throughput.”