Join a top-tier financial regulatory body dedicated to maintaining regional monetary stability. The organization is currently undergoing a multi-year digital transformation, modernizing its enterprise IT landscape through a massive investment in AI and simplified digital platforms.
about the team.You will join a high-impact AI & Innovation team that serves as the organization’s engine for technical evolution. This group is specifically focused on the intersection of innovation and integrity—ensuring that the next generation of Agentic AI and LLM applications are built on a foundation of reliability, security, and world-class quality standards.
about the job.As a QA Engineer (AI & Innovation), your mission is to design and maintain advanced quality assurance solutions for AI platforms. Beyond traditional testing, you will play a pivotal role in AI Governance, building enterprise guardrails and evaluation tools to ensure that AI deployments are compliant, reliable, and high-performing.
AI Quality & Governance: Integrate AI/GenAI models (e.g., RAG, LLMs) into production and lead the evaluation of AI guardrails using frameworks like RAGAS, Promptfoo, or LangSmith.
Full-Stack Testing: Develop and maintain automated testing solutions for full-stack applications (React/Node.js/Postgres), ensuring high performance and security.
DevSecOps Integration: Design and operate GitLab CI/Jenkins pipelines, embedding automated test execution, security scanning, and containerized deployments.
System Reliability: Diagnose production issues through root-cause analysis and continuously optimize system uptime and reliability.
Knowledge Excellence: Document complex architectures, API test plans, and deployment processes to ensure audit readiness and seamless knowledge sharing.
Professional Experience: 4+ years in QA testing with a strong focus on automated processes and modern testing frameworks (Cypress, Selenium, or Playwright).
Technical Stack: Hands-on proficiency in JavaScript/TypeScript (React/Next) and Node.js is required.
AI Evaluation (Highly Preferred): Experience in AI governance assessments and familiarity with AI frameworks such as LangChain, PyTorch, or TensorFlow.
Cloud & Infrastructure: Solid understanding of AWS/Azure, Kubernetes, and Infrastructure-as-Code (Terraform/Ansible).
Automation Mastery: Proven track record in building CI/CD pipelines, container builds, and automated environment promotion.
Industry Background: Experience in financial services or regulated international environments is a significant plus, along with a data-driven approach to problem-solving.
