QA Engineer (AI-Powered Testing & Automation)

We are seeking a highly motivated and hands-on QA Engineer who possesses deep expertise in traditional QA processes and has actively integrated Generative AI & Modern AI Tools into their daily testing workflows.

In this role, you won't just run tests manually; you will act as an "AI" tester—leveraging advanced tooling to draft test cases, generate mock API payloads, execute functional sweeps, and automate repetitive tasks. You will be a critical guardian of our platform’s reliability, ensuring high-quality releases across our complex database configurations, client integrations, and consumer portals.

We are seeking a highly motivated and hands-on QA Engineer who possesses deep expertise in traditional QA processes and has actively integrated Generative AI & Modern AI Tools into their daily testing workflows.

In this role, you won't just run tests manually; you will act as an "AI" tester—leveraging advanced tooling to draft test cases, generate mock API payloads, execute functional sweeps, and automate repetitive tasks. You will be a critical guardian of our platform’s reliability, ensuring high-quality releases across our complex database configurations, client integrations, and consumer portals.

Key Responsibilities

• End-to-End QA Ownership: Define, develop, and execute comprehensive test plans, structured test cases, generate data for performance testing and functional testing, and test suites for complex financial technology systems.
• AI-Driven Test Engineering: Actively utilize AI assistants and tools (e.g., GitHub Copilot, Claude, ChatGPT, Gemini, or specialized QA AI agents) to rapidly generate edge-case test scenarios, synthesize complex test data, and write code snippets.
• API & Integration Testing: Perform rigorous API testing using Postman, or code-based tools, leveraging AI to construct mock JSON/XML payloads, parameterize variables, and automate assertions.
• Functional & UI Testing: Execute detailed functional testing of our web applications and portals, ensuring seamless user experiences and logical interface workflows.
• Data Validation & SQL Sweeps: Perform database testing on relational databases (PostgreSQL/SQL Server) to verify that background system changes, audit triggers (e.g., consent changes, CND compliance), and data scrubbing configurations map accurately.
• Defect Lifecycle Management: Identify, isolate, document, and track software defects in Jira, Provide developers with detailed steps to reproduce, raw logs, payload snippets, and clear impact definitions.
• Collaboration: Partner closely with Product Managers, Business Analysts, and Software Engineers to clarify requirements and establish robust Acceptance Criteria early in the sprint cycle.

**Technical Requirements & Tooling

• Traditional QA Foundations:Deep understanding of the Software Development Life Cycle (SDLC), Software Testing Life Cycle (STLC), regression testing, and Agile Scrum methodologies.
• AI for QA Tools: Hands-on experience using AI-powered tools (e.g., GitHub Copilot, ChatGPT, Tabnine, Testim.io, or Tricentis) specifically optimized for:
o Drafting and optimizing written test cases.
o Synthesizing complex mock datasets.
o Explaining code logic or generating test automation scripts.
o API Testing: High proficiency with Postman or Insomnia (writing test scripts inside Postman, environment variables, runner collections).
o Database Skills: Strong SQL queries capability (Joins, Unions, conditional filters) to inspect and validate tables.
o Project Management & Version Control: Experience using for bug tracking and sprint alignment, and Git/GitHub for basic version control.

Education : Bachelor’s degree in Computer Science, Information System, or related disciplines.

Experience : 5+ years of experience in in traditional QA processes and Integrated Generative AI & Modern AI Tools.