Quality Engineer

global leader in financial technology, powering mission - critical systems that help the world pay, bank, and invest. If you re passionate about advancing the future of fintech and building transformative products used across the money lifecycle, we d like to ask you

About the team:

Revenue Connect is next-generation cloud platform, designed to transform commercial pricing and billing for banks with modern AWS infrastructure, API-first microservices, and advanced UI/UX. This approach eliminates legacy technical debt and delivers the speed, accuracy, and transparency banks demand.

As Quality Engineering Lead, you ll drive uncompromising reliability and intelligent automation, using AI-powered insights and automation-first engineering to ensure our platform s excellence and robust validation at every layer.

What you will be doing:

• Design, build, and maintain automation frameworks for UI, API, data, and microservices testing.

• Leverage AI-driven techniques for test generation, defect detection, and regression selection.

• Develop and track observability-based quality metrics and CI/CD quality gates.

• Validate AI/ML-powered features and collaborate to ensure safe and correct model behavior.

• Define and implement end-to-end quality strategies across key platform components.

• Partner with engineering, product, and SRE teams to ensure strong SDLC testability and guardrails.

• Lead and mentor a quality engineering team, fostering AI-assisted engineering practices.

• Drive technical excellence through standards, code reviews, and continuous skill development.

What you will need:

• Bachelors degree in Computer Science or equivalent experience.

• 7+ years of direct experience in software quality engineering, including automation architecture and framework development.

• Strong hands - on expertise with modern automation tools (Playwright, Selenium, JUnit/TestNG, Postman et al).

• Proven experience validating AI - enabled features - LLMs, anomaly detection, model - driven logic, or generative workflows.

• Deep knowledge of testing for distributed systems, microservices, data pipelines, and cloud environments (AWS preferred).

• Solid experience integrating automation into CI/CD pipelines.

• Strong debugging, problem - solving , and analytical skills across frontend, backend, and data layers.

• Excellent communication, collaboration, and cross - team influence skills in a fast - paced engineering organization.

Added bonus if you have:

• Experience with RAG pipelines, vector stores, guardrail frameworks, model evaluation, or safe AI patterns.

• Experience testing financial systems, billing engines, or analytics - heavy platforms.

• Familiarity with synthetic data generation or statistical validation for AI and data - driven testing.

What we offer you:

you can learn, grow and make an impact in your career. Our benefits include:

Flexible and creative work environment

Diverse and collaborative atmosphere

Professional and personal development resources

Opportunities to volunteer and support charities

Competitive salary and benefits

• Bachelors degree in Computer Science or equivalent experience.

• 7+ years of direct experience in software quality engineering, including automation architecture and framework development.

• Strong hands - on expertise with modern automation tools (Playwright, Selenium, JUnit/TestNG, Postman et al).

• Proven experience validating AI - enabled features - LLMs, anomaly detection, model - driven logic, or generative workflows.

• Deep knowledge of testing for distributed systems, microservices, data pipelines, and cloud environments (AWS preferred).

• Solid experience integrating automation into CI/CD pipelines.

• Strong debugging, problem - solving , and analytical skills across frontend, backend, and data layers.

• Excellent communication, collaboration, and cross - team influence skills in a fast - paced engineering organization.

Added bonus if you have:

• Experience with RAG pipelines, vector stores, guardrail frameworks, model evaluation, or safe AI patterns.

• Experience testing financial systems, billing engines, or analytics - heavy platforms.

• Familiarity with synthetic data generation or statistical validation for AI and data - driven testing.