Vetted Cursor (AI Code Editor) Professionals

“Full-stack engineer with hands-on ownership of production systems, including a Kafka-based notification/alerting platform (Node.js + React) deployed on AWS with Docker/GitHub Actions, achieving ~95% email delivery reliability. Demonstrates strong operational maturity (observability, CI/CD, zero-downtime migrations) and experience shipping in ambiguous environments (SJSU project) with evolving requirements.”

“Early-career product designer with strong end-to-end ownership on a thesis product, Klaro—a smartwatch-led gym guidance experience for beginners focused on reducing hesitation and anxiety in the moment. Stands out for combining UX craft with scrappy product validation, including a 14% waitlist conversion test and a navigation experiment that helped users reach equipment about 40% faster.”

Krystal Galdamez

Screened

Junior Full-Stack Engineer specializing in AI-powered web applications

San Francisco, CA1y exp

“Startup-focused engineer who has shipped Python backend features, AI integrations, and Playwright automation for products including an AI coaching platform and hiring workflow tools. Stands out for working through ambiguous zero-spec environments, hardening flaky Firebase-authenticated test flows, and designing practical fallback paths when AI outputs are unreliable.”

“Software engineer building AI-powered automation features in commercial real estate, including brochure generation and property listing workflows. They combine FastAPI/Redis/Celery backend architecture with multi-agent LLM design, structured prompting, testing, and production monitoring, and are now actively learning RAG and vector databases to make outputs more personalized.”

“Solo builder of ZenDSA, a live AI-powered DSA learning product with 37 real users, built end to end using Java/Spring Boot, React, and TypeScript. Particularly interesting for teams building AI products: they designed a production LLM fallback architecture, enforced structured JSON outputs, monitored parse-failure regressions, and fixed an SSRF vulnerability after launch.”

“Unity game developer who implemented a swipe-based pack-slicing minigame in "Herois da Fruta," improving responsiveness by evaluating both swipe start and end positions. Has multiplayer AR experience on "ARcade Sports" using Photon Unity Network to sync four AR devices, including coordinating AR anchors with online communication and camera/world alignment. Prefers collaborative teams and a 9-to-5 schedule; targets €17k–€20k depending on responsibilities and benefits.”

Abhay Bisht

Screened

Junior Software Engineer specializing in AI and full-stack SaaS

Bangalore, India2y exp

“AI-first developer who reports using agents for roughly 85% of coding work, with a disciplined process centered on detailed specs, prompt design, review, and testing. Has built a personal multi-agent orchestration setup with specialized agents for testing, PR extraction, review, and synthesis, and stays current through AI engineering newsletters and a network of AI companies.”

“Backend engineer who built and scaled a FastAPI-based backend for an AI-driven maintenance system automating vendor sourcing/bidding/communication. Emphasizes async, message-driven architecture with strong observability and state-machine-driven workflows, plus robust webhook/idempotency patterns to prevent duplicate/out-of-order events from causing bad bids or state changes.”

“Frontend engineer with strong experience building enterprise-grade banking interfaces, including a cross-platform credit card application with secure document uploads, real-time status tracking, and complex multi-step e-forms. Stands out for combining React/TypeScript architecture skills with deep browser-level debugging and measurable UX improvements in regulated financial environments.”

Ahmad Rayyan

Screened

Entry-level Full-Stack Engineer specializing in Applied AI and multi-agent systems

Pakistan1y exp

“Built both traditional full-stack products and advanced LLM systems, from a React/Flask dashboard used by instructors to monitor GitHub contribution patterns to multi-agent benchmark infrastructure at Analytiverse. Particularly strong in evaluation-heavy AI engineering: designed executable verifiers, force-zero anti-reward-hacking checks, and token-optimization strategies that delivered a 40-point pass-rate lift and 90x token reduction on SwarnBench tasks.”