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Vetted TestNG Professionals
Pre-screened and vetted.
Mid-level QA Automation Engineer specializing in enterprise test automation for FinTech and industrial systems
Mid-level Java Full-Stack Developer specializing in enterprise SaaS platforms
Mid-Level Software Engineer specializing in Go microservices, cloud-native systems, and AI integration
Mid-level Java Full-Stack Developer specializing in cloud-native microservices
Mid-level Software Engineer specializing in backend systems, data pipelines, and GenAI automation
Senior QA Lead and Software Test Engineer specializing in test automation and enterprise QA
Mid-Level Full-Stack Software Engineer specializing in FinTech and Healthcare
Mid-level QA Automation/SDET Engineer specializing in FinTech and E-commerce test automation
Mid-level Full-Stack Java Developer specializing in microservices and cloud platforms
Senior QA Automation Engineer specializing in web, mobile, and API test automation
Senior QA Engineer specializing in test automation and enterprise web/API quality
Mid-level Full-Stack Engineer specializing in cloud-native microservices
Mid-level Full-Stack Developer specializing in Java Spring Boot microservices and React
Senior Full-Stack Software Engineer specializing in Java/Spring Boot and AWS
Mid-Level Software Engineer specializing in cloud-native distributed systems
Vamsi M
Senior QA Automation Engineer specializing in Playwright UI and API test automation
“QA automation engineer with American Express experience owning an end-to-end UI regression suite for critical payment/transaction workflows. Rebuilt the suite with Playwright (BDD/TestNG/POM) and integrated it into CI to catch release-blocking issues like UI/backend payment mismatches and session timeout defects, and applies risk-based test strategy including MFA payment flows.”
Sai Prasanth Guthula
Mid-level Software Engineer specializing in backend systems for FinTech and SaaS
“Amazon engineer with a blend of backend platform and applied AI experience, spanning Kafka/Spring Boot/Django financial workflows and internal LLM-powered RAG systems for reconciliation investigations. Stands out for owning deployments end-to-end, improving reliability in high-volume transaction processing, and adding practical guardrails like confidence checks and human review to production AI workflows.”
Nicolas Collins
Senior Full-Stack Engineer specializing in AI and cloud-native applications
“Built and shipped a production LLM-powered internal developer tool that accelerated code reviews by about 30% while maintaining reliability through modular orchestration, validation, and monitoring. Demonstrates strong practical depth in agent architecture, backend workflow orchestration, and observability for non-deterministic AI systems, with concrete examples of reducing agent errors by 60%.”