Remote

Quality Assurance Engineer (for AI Agent)

Design and run end-to-end testing and manual QA processes for our web applications and AI agent.

Key responsibilities

Test strategy & execution: design, develop, and execute comprehensive end-to-end (e2e) test suites using TypeScript for our web applications and services.
Manual QA process: establish, document, and continuously refine manual QA processes, test plans, and test cases to cover all critical functionalities and user flows.
Defect management: identify, document, prioritize, and track software defects, working closely with development teams to ensure timely resolution.
Collaboration: collaborate effectively with product managers, developers, and other stakeholders throughout the software development lifecycle to ensure quality is embedded from conception to deployment.
Regression testing: perform thorough regression testing when bugs are resolved and new features are implemented.
Performance & security: contribute to performance, load, and security testing efforts as needed.
Process improvement: proactively identify areas for improvement in our QA methodologies, tools, and processes, and implement best practices.
Reporting: generate clear and concise QA reports, providing insights into product quality and testing progress.

Experience: proven experience in Quality Assurance or Software Testing roles within a technology-driven environment.
Technical skills: strong proficiency in writing and maintaining end-to-end (e2e) tests using TypeScript.
QA methodologies: solid understanding of the software development lifecycle and various QA methodologies (e.g. Agile, Scrum).
Self-organization: exceptional organizational skills with the ability to manage multiple priorities, work independently, and meet deadlines in a dynamic environment.
Process establishment: demonstrated capability to set up, document, and implement effective manual QA processes from scratch or improve existing ones.
Problem-solving: excellent analytical and problem-solving skills with meticulous attention to detail.
Communication: strong verbal and written communication skills, with the ability to articulate technical issues clearly to both technical and non-technical audiences.

LLM/chat agents: understanding of Large Language Models (LLMs) and chat agent technologies - and how to QA AI agents.
Domain knowledge: familiarity with legal technology products or the legal industry.
Automation tools: experience with other test automation frameworks and tools (e.g. Playwright, Cypress, Selenium).
CI/CD: experience integrating QA processes into Continuous Integration/Continuous Deployment (CI/CD) pipelines.
Cloud platforms: familiarity with cloud platforms (e.g. AWS, Azure, GCP).