Vetted Manual Testing Professionals

“QA engineer with 11+ years (nearly 12) in IT across financial, healthcare, and telecommunications domains, experienced partnering closely with developers throughout Agile delivery. Strong in building/maintaining living test plans, running smoke/regression on new builds, and driving triage with impact-based prioritization using Jira/TestRail/Confluence; targets $100k+ base with standard benefits.”

“QA automation engineer with hands-on ownership of Selenium (C#) and Cypress (JavaScript) suites, including CI integration in GitLab with PR smoke gating and nightly regressions with JUnit reports/screenshots. Drove a reported ~60% reduction in manual effort, improved suite maintainability through reuse/merging tests, and proactively shaped requirements/acceptance criteria in sprint planning to prevent defects (including claims calculation and server/log-related issues).”

“AI-native software developer who has built a highly structured workflow around Claude, Cursor, design agents, and SpecKit to plan, design, implement, and test features end to end. They also use multi-agent setups with sub-agents and git worktrees, and have experience acting as a tech lead for AI agents by assigning roles, guiding execution, and reviewing outputs.”

Zain Abedin

Screened

Mid-level Software Engineer specializing in web platforms, mapping, and identity systems

Vancouver, Canada5y exp

“Full-stack engineer with strong backend and data architecture depth, including building a TypeScript/React/Node/MongoDB DNS resolver with cycle detection and recursive graph traversal. They speak credibly about production performance tuning, distributed database migration, and message-queue reliability patterns, with cited impact including 30% faster DNS queries, P95 retrieval improved from 30+ seconds to ~2 seconds, and 200% higher concurrent-user capacity.”

“QA/project leader with ~19 years experience running high-profile, multi-million-dollar software initiatives and driving quality through disciplined milestone gates (Alpha/Beta/FC/GM), regression planning, and weekly bug scrubs. JIRA-centric practitioner (Zephyr/Confluence) who partners closely with engineering, automation, documentation, marketing, and sustaining teams—including offshore collaboration—to unblock testers and improve diagnostics for difficult issues like memory leaks.”

“QA automation engineer who owned an end-to-end test suite for a financial payments application, building cross-layer E2E coverage (UI/API/DB) and integrating it into CI with smoke-on-commit and nightly regression. Caught high-impact issues including duplicate payments caused by missing idempotency in backend retry logic and an RBAC authorization gap, and has hands-on experience stabilizing flaky Cypress tests via network-call synchronization.”

Joon Im

Screened

Mid-level QA Automation Engineer (SDET) specializing in API and test automation

Los Alamitos, CA4y exp

“QA automation engineer who owns and modernizes end-to-end test automation across Selenium (Java) and Cypress (JavaScript), integrating suites into GitLab CI/CD with PR gating, nightly runs, and Sauce Labs reporting/recordings. Demonstrated impact by catching a session-timeout workflow issue in CI that manual testing missed and by reducing flakiness through stack upgrades, coding standards, and API-synchronized assertions.”

“Built both a React/Supabase kanban product and CodeVoyage, a multi-agent platform for navigating large TypeScript/Node.js codebases. Stands out for being unusually rigorous about AI-assisted development: they quantify AI usage, manually verify generated code, and have firsthand experience debugging failures in persistence layers, retrieval quality, and long-context agent orchestration.”

Andreas Haryono

Screened

Senior Technical Project Manager specializing in game development QA and SDK releases

Sukoharjo, Central Java, Indonesia13y exp

“Game tester with hands-on QA experience primarily on mobile and PC titles, looking to transition into console testing. Emphasizes critical-path prioritization (e.g., crashes) and uses AI-driven R&D to ramp quickly while reviewing test cases and masking sensitive data.”