Remote Quality Assurance Engineer

Position Overview

A Quality Assurance Engineer is a corporate function within the Engineering organization responsible for ensuring the quality, reliability, and release-readiness of software products built on modern technologies, including cloud-native applications hosted on Microsoft Azure and AI/ML-enabled features.

Major Responsibilities or Assigned Duties

• Participate in the test management lifecycle, including test planning, execution tracking, defect management and reporting.
• Provide input on release readiness criteria to Engineering and Product stakeholders.
• Maintain the regression suite after every release.
• Develop and maintain automated test suites in Python (e.g., pytest) and JavaScript/Node.js, integrated into CI/CD pipelines.
• Write and review complex SQL queries, joins, and aggregations to validate data accuracy, completeness, and reconciliation across systems.
• Validate data flows across source systems, transformation layers, and reporting/consumption layers.
• Ensure test data supports both functional automation and AI/ML/RAG evaluation needs.
• Design and execute test strategies for AI/ML and Retrieval-Augmented Generation (RAG) pipelines and AI-assisted features, including retrieval accuracy, grounding, hallucination, output quality, bias/safety, and drift (regression) checks.
• Build and maintain automated evaluation harnesses and datasets for AI/ML features, including prompt/response scoring and metric tracking.
• Validate applications, APIs, and test environments deployed on on-prem data center, Microsoft Azure, including Azure-hosted services, data stores, and CI/CD pipelines.
• Write detailed test cases and test plans that trace directly to code paths, business rules, and acceptance criteria.
• Partner with developers during code review to flag insufficient test coverage, untested branches, and high-risk changes before merge.
• Perform post-deployment validation to confirm application, API, and AI feature stability in production.
• Investigate production defects and data issues, perform root cause analysis, and drive resolution with Engineering.

Requirements

• 5+ years of experience in automated software testing
• 5+ years of experience in manual software testing
• 5+ years of experience in component-level testing
• 5+ years of experience in end-to-end testing
• At least 5 years of experience in SQL
• At least 3 years of experience in React
• At least 3 years of experience in Node.js
• At least 3 years of experience with Python source code in GitLab
• At least 2 years of experience testing AI/ML
• At least 2 years of experience evaluating AI/ML
• At least 2 years of experience testing Retrieval-Augmented Generation (RAG)
• At least 2 years of experience testing generative AI features
• At least 2 years of experience testing workloads on Microsoft Azure