Software Engineer in Test II

About Bright Money

Bright Money is a consumer fintech built for middle-income consumers. Our platform helps consumers build credit, manage debt, and access suitable loans and credit cards - addressing the key financial needs of people living paycheck to paycheck.

Bright is a profitable, India-built fintech serving the U.S. market, with a clear trajectory toward $100 million in revenue. Our business model combines subscription revenue with a financial-services marketplace across loans, credit cards, and credit-building solutions.

We have launched an AI-powered money assistant and agentic AI experiences that simplify access to credit. Our ambition is to build the first AI-driven consumer-fintech platform for middle-income consumers.

Founded in 2019, Bright’s founding team includes leaders from McKinsey’s Banking Practice - Petko Plachkov and Avi Patchava - and data science leaders from InMobi. Bright is backed by leading global venture capital firms and technology investors across the U.S., Europe, and Asia.

With a data-driven, high-ownership, and fast-paced culture, we are building a global consumer-fintech company from India.

What is the role about?

We are looking for an SDET - II to contribute to quality engineering for Bright’s consumer app and platform. You will help build, execute, and maintain the automation frameworks that our mobile, API, and web testing runs on, ensuring quality gates are met in our release pipelines.

This is a hands-on, independent technical role focused strongly on automation. You will write test code every week, execute test strategies, collaborate closely with developers, and put AI to work in your daily testing workflow to ensure we ship high-quality products to our customers.

What will you do?

• Automation execution & frameworks: Contribute to the development and maintenance of scalable automation frameworks across mobile, API, and web layers.
• Mobile & API coverage: Build and execute end-to-end automated tests for the Bright app (iOS and Android) and backend services, covering functional, integration, and regression suites.
• CI/CD & release quality: Monitor and maintain automated tests integrated into CI/CD pipelines. Analyze test execution results, assist in defect triage, and perform root-cause analysis for failures.
• Shift-left engagement: Participate in design discussions and test planning to ensure early defect detection and adequate test coverage.
• Non-functional testing: Assist in the execution of performance, load, security, and resilience tests alongside the broader engineering team.
• Quality metrics: Track automation coverage, report test results, and log escaped defects to maintain visibility on application health.
• AI-assisted testing: Use GenAI tools to accelerate script generation, brainstorm edge cases, and improve daily productivity while maintaining a critical eye for validating AI-generated output.

Ideal candidate profile

Experience & Background:

• Experience: 2-4 years in software testing and quality engineering, with a strong focus on automation-driven roles.
• Automation Skills: Strong hands-on experience in writing automation scripts and working within established frameworks (such as Appium, Espresso, or XCUITest for mobile; REST Assured or pytest for APIs; Selenium or Playwright for web).
• Programming: Basic knowledge in programming (Java, Kotlin, or JavaScript/TypeScript) to understand application codebases and write reliable test scripts.
• CI/CD & tooling: Familiarity with Git, Jenkins or GitHub Actions, and test reporting tools. Comfortable analyzing logs and debugging pipeline failures.
• Backend & data: Basic understanding of SQL and API debugging.
• Domain: Experience in fintech, payments, or another regulated, high-reliability environment is a strong plus.

Preferred Qualifications:

• Immediate joiners are a strong plus.
• Basic knowledge in Python is highly preferred.
• Knowledge of using GenAI (like Claude, ChatGPT, Copilot, etc.) for test case design, script generation, and productivity enhancement.

Mindset & Operating DNA:

• Quality focus: Takes end-to-end responsibility for the quality of the features they test, rather than just executing test cases.
• Automation bias: Instinctively looks to remove repetitive manual effort and writes automation to solve testing bottlenecks.
• Pragmatism: Prioritizes testing based on risk and user impact.
• Collaboration: Works smoothly with developers and product …