Quality Assurance Engineer - Financial Industry (Ref: QAE/HL)

Our client is a reputable and leading Financial Institution in Hong Kong. In order to meet their business expansion, they are seeking a Quality Assurance Engineer to join their team.

Responsibilities:

Work closely with data scientists and AI engineers to integrate AI / Generative-AI models (e.g., Retrieval-Augmented Generation, LLMs) into production applications.

Design, develop and maintain full-stack web applications (front-end, back-end and database) ensuring high performance, scalability and security.

Design and operate CI/CD pipelines (GitLab CI, Jenkins) integrating unit, integration, and automated test execution, artefact management, security scanning, and deployments to multiple environments.

Diagnose and resolve production issues, perform root-cause analysis and continuously improve system reliability.

Contribute to agile ceremonies, provide accurate effort estimates and keep stakeholders updated on progress.

Document architecture, APIs, deployment processes and test plans to ensure knowledge sharing and audit readiness.

Stay current with emerging technologies; introduce best practices to the team.

Requirements:

Bachelor's degree in Information Systems, Information Technology, Computer Science, Engineering, or related disciplines.

At least 4 years of experience in quality assurance testing, preferably with banking or financial service background.

Strong understanding of the following processes and tooling:

o Test frameworks (Cypress, Selenium, Playwright).

o Test management tools (TestRail, Zephyr or similar).

o Front-end: JavaScript/TypeScript and React, Angular or Next

o Back-end: Node.js o Database: Postgres

Experience in AI governance related assessment is highly preferred, including evaluation of AI guardrails, evaluation framework such as RAGAS, Promptfoo, LangSmith, etc.

Proven experience building and maintaining GitLab CI or Jenkins pipelines, including automated testing, container builds and environment promotion.

Experience with Infrastructure-as-Code (Terraform, Ansible Playbook).

Solid understanding of cloud platforms (AWS / Azure / GCP) and container orchestration with Kubernetes.

Knowledge of AI / ML frameworks (TensorFlow, PyTorch, LangChain or similar) and best practices for integrating models into microservices is a plus.

Self-motivated and innovative with strong analytical, problem-solving, and interpersonal skills.

Team player with excellent communication skills in both verbal and written English and Chinese.

For all applications, kindly send us your updated CV quoting reference QAE/HL.

Full-time