AI-Powered QA Engineer

TikTok

Singapore

On-site

SGD 120,000 - 180,000

Full time

14 days+

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Job summary

TikTok is seeking a Software Test Engineer (AI) to advance quality, reliability, and security for its products at global scale. You will design AI-powered testing solutions, automate testing, and drive quality improvements across the development lifecycle.

Work with cross-functional teams to apply LLMs and AI agents to testing, bug analysis, and engineering productivity. Stay abreast of AI advancements to shape next-generation testing capabilities at TikTok.

Qualifications

Bachelor's degree or above in Computer Science, Software Engineering, Information Technology, or a related technical discipline.
Experience in software quality assurance or software testing, preferably for mobile applications, backend services, or distributed systems.
Solid understanding of software testing methodologies, debugging, and quality assurance best practices across the software development lifecycle.
Familiarity with distributed systems and fundamental knowledge of iOS and/or Android platforms.
Experience with one or more testing domains, including automation testing, performance testing, or test platform/tool development.
Strong interest in Generative AI and Large Language Models (LLMs), with an understanding of common LLM capabilities and real-world application scenarios.
Excellent analytical and problem-solving skills, with the ability to collaborate effectively across cross-functional and global teams.
Passion for building high-quality products and driving end-to-end quality assurance through AI-powered testing technologies.

Responsibilities

Design and develop AI-powered testing solutions that improve software quality and engineering efficiency across the entire software development lifecycle.
Work on quality and engineering efficiency initiatives leveraging LLMs, including change risk analysis, automated testing, search quality evaluation, and LLM security testing.
Identify quality and engineering efficiency pain points in collaboration with software and algorithm engineering teams, propose practical optimization solutions, and drive their implementation to improve product quality and engineering efficiency.
Stay up to date with the latest advancements in Large Language Models (LLMs) and AI-generated content technologies, explore innovative quality and engineering efficiency solutions for software testing, and refine them through practical application.