Senior Software Test Engineer

Job Description The QA Tester would be responsible for quality validation of a cloud-native, containerized AWS platform supporting Insider 2.0, Scoring Portal, Tech Match, RFI Manager, and Vendor Directory. The role covers application QA, data validation, analytics validation, regression testing, job monitoring, AI-assisted QA, and release-readiness support for a data-intensive SaaS platform built on Python/Flask, React, Plotly Dash, Aurora MySQL, Pandas, Dagster, and AWS ECS. Responsibilities Understand the values and vision of the organization Protect the Intellectual Property Adhere to all the policies and procedures Define test strategy, test plans, test scope, and release-readiness criteria for applications Create and manage feature, regression, smoke, and end-to-end test plans in VersionOne or similar Agile ticketing systems Execute feature validation, regression testing, exploratory testing, and UAT support across data-driven workflows Validate acceptance criteria, document defects, and drive retest and closure workflows with risk-based testing and coverage tracking Validate data ingestion, scoring, benchmarking, analytics, and dashboard workflows including SQL-based data validation Monitor jobs, pipeline status, and Dagster runs; perform log review and environment-level troubleshooting Validate API responses, payloads, and system workflows at a functional level Apply AI-assisted test generation, test maintenance, and regression optimization using Codex or similar AI coding tools Maintain test evidence, traceability, and release signoff practices; support release checkpoints and quality metrics Cross-train and provide QA coverage as needed. Essential Skills Job 6-8 years of experience in QA, software testing, or quality engineering Experience defining test strategy, test plans, test scope, and release-readiness criteria Experience creating and managing feature, regression, smoke, and end-to-end test plans in VersionOne or similar Agile ticketing systems Experience executing feature validation, regression testing, exploratory testing, and UAT support Experience with risk-based testing, defect triage, and coverage tracking Experience validating acceptance criteria, documenting defects, and driving retest/closure workflows Understanding of test evidence, traceability, and release signoff practices Working knowledge of SQL for test data validation, troubleshooting, and basic database queries Familiarity with job monitoring, pipeline status checks, logs, and environment-level troubleshooting Ability to validate API responses, payloads, and system workflows at a functional level Experience operating in Agile delivery models such as Scrum and Kanban Experience with VersionOne, Jira, or equivalent ticketing systems for defect tracking and sprint support Understanding of Test Ops concepts, including test execution visibility, release checkpoints, and quality metrics Personal Excellent communication and interpersonal skills, with the ability to coordinate with product, development, and business stakeholders Strong attention to detail with disciplined test evidence and traceability practices A proactive approach to problem solving and release-readiness ownership Willingness to adopt new AI-assisted tools and continuously improve QA practices Preferred Skills Job Exposure to using Codex or similar AI coding tools to accelerate automated test creation Familiarity with AI-assisted test generation, test maintenance, and regression optimization Understanding of future-state QA automation approaches such as AI-generated test cases, self-healing automation, and intelligent test selection Familiarity with Dagster run monitoring and data pipeline validation Experience supporting release cycles for data-driven or SaaS applications Personal Demonstrate proactive thinking Strong interpersonal relations and stakeholder coordination skills Ability to work under stringent deadlines and demanding client conditions Other Relevant Information Bachelor's degree in Computer Science, Information Technology, or a related field 6-8 years of experience in QA or quality engineering, preferably for data-driven or SaaS applications Willingness to cross-train and provide QA coverage across multiple applications