Software Test Engineer (AI), TikTok
Sep 21, 2026 Singapore
About us
TikTok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy.
- Size: 5,001 - 10,000 employees
- Industry: Entertainment & Gaming
Responsibilities
The TikTok Engineering Test Team is dedicated to ensuring the quality, reliability, and security of TikTok's products at global scale. We partner closely with software engineers, algorithm engineers, and product teams to accelerate feature delivery while maintaining exceptional product quality.
Our team is redefining how quality assurance is built. We leverage Large Language Models (LLMs), AI agents, and intelligent automation to reimagine the entire testing lifecycle-from test design and execution to bug analysis, quality evaluation, and engineering productivity. Our mission is to build next-generation AI-powered testing capabilities that enable faster, smarter, and more scalable software delivery. Joining our team and working at the intersection of Software Engineering, Quality Engineering, and Generative AI, helping shape the future of AI-native software testing at TikTok.
As a Software Test Engineer (AI), you will:
- 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 AIGC technologies, explore innovative quality and engineering efficiency solutions for software testing, and continuously refine them through practical application.
Qualifications
Minimum 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.
Preferred Qualifications
- Proficiency in one or more programming languages such as Java, Python, Go, or Objective-C.
- Experience developing test automation frameworks, testing platforms, or engineering productivity tools.
- Familiarity with distributed infrastructure and cloud-native technologies such as Redis, Kafka, Docker, Kubernetes, Hive, Spark, NSQ, or ZeroMQ.
- Hands-on experience with AI-related projects, including LLM application development, AI agent evaluation, model evaluation, AI-assisted testing, or AI testing frameworks.
- Experience leveraging AI tools (e.g. LLMs, AI coding assistants, or AI agents) to improve testing efficiency, automate test case generation, bug analysis, or software quality workflows.
The TikTok Engineering Test Team is dedicated to ensuring the quality, reliability, and security of TikTok's products at global scale. We partner closely with software engineers, algorithm engineers, and product teams to accelerate feature delivery while maintaining exceptional product quality.
Our team is redefining how quality assurance is built. We leverage Large Language Models (LLMs), AI agents, and intelligent automation to reimagine the entire testing lifecycle-from test design and execution to bug analysis, quality evaluation, and engineering productivity. Our mission is to build next-generation AI-powered testing capabilities that enable faster, smarter, and more scalable software delivery. Joining our team and working at the intersection of Software Engineering, Quality Engineering, and Generative AI, helping shape the future of AI-native software testing at TikTok.
As a Software Test Engineer (AI), you will:
- 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 AIGC technologies, explore innovative quality and engineering efficiency solutions for software testing, and continuously refine them through practical application.
Minimum 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.
Preferred Qualifications
- Proficiency in one or more programming languages such as Java, Python, Go, or Objective-C.
- Experience developing test automation frameworks, testing platforms, or engineering productivity tools.
- Familiarity with distributed infrastructure and cloud-native technologies such as Redis, Kafka, Docker, Kubernetes, Hive, Spark, NSQ, or ZeroMQ.
- Hands-on experience with AI-related projects, including LLM application development, AI agent evaluation, model evaluation, AI-assisted testing, or AI testing frameworks.
- Experience leveraging AI tools (e.g. LLMs, AI coding assistants, or AI agents) to improve testing efficiency, automate test case generation, bug analysis, or software quality workflows.
The TikTok Engineering Test Team is dedicated to ensuring the quality, reliability, and security of TikTok's products at global scale. We partner closely with software engineers, algorithm engineers, and product teams to accelerate feature delivery while maintaining exceptional product quality.
Our team is redefining how quality assurance is built. We leverage Large Language Models (LLMs), AI agents, and intelligent automation to reimagine the entire testing lifecycle-from test design and execution to bug analysis, quality evaluation, and engineering productivity. Our mission is to build next-generation AI-powered testing capabilities that enable faster, smarter, and more scalable software delivery. Joining our team and working at the intersection of Software Engineering, Quality Engineering, and Generative AI, helping shape the future of AI-native software testing at TikTok.
As a Software Test Engineer (AI), you will:
- 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 AIGC technologies, explore innovative quality and engineering efficiency solutions for software testing, and continuously refine them through practical application.
Qualifications
Minimum 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.
Preferred Qualifications
- Proficiency in one or more programming languages such as Java, Python, Go, or Objective-C.
- Experience developing test automation frameworks, testing platforms, or engineering productivity tools.
- Familiarity with distributed infrastructure and cloud-native technologies such as Redis, Kafka, Docker, Kubernetes, Hive, Spark, NSQ, or ZeroMQ.
- Hands-on experience with AI-related projects, including LLM application development, AI agent evaluation, model evaluation, AI-assisted testing, or AI testing frameworks.
- Experience leveraging AI tools (e.g. LLMs, AI coding assistants, or AI agents) to improve testing efficiency, automate test case generation, bug analysis, or software quality workflows.
Responsibilities
ResponsibilitiesThe TikTok Engineering Test Team is dedicated to ensuring the quality, reliability, and security of TikTok's products at global scale. We partner closely with software engineers, algorithm engineers, and product teams to accelerate feature delivery while maintaining exceptional product quality.
Our team is redefining how quality assurance is built. We leverage Large Language Models (LLMs), AI agents, and intelligent automation to reimagine the entire testing lifecycle-from test design and execution to bug analysis, quality evaluation, and engineering productivity. Our mission is to build next-generation AI-powered testing capabilities that enable faster, smarter, and more scalable software delivery. Joining our team and working at the intersection of Software Engineering, Quality Engineering, and Generative AI, helping shape the future of AI-native software testing at TikTok.
As a Software Test Engineer (AI), you will:
- 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 AIGC technologies, explore innovative quality and engineering efficiency solutions for software testing, and continuously refine them through practical application.
Qualifications
QualificationsMinimum 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.
Preferred Qualifications
- Proficiency in one or more programming languages such as Java, Python, Go, or Objective-C.
- Experience developing test automation frameworks, testing platforms, or engineering productivity tools.
- Familiarity with distributed infrastructure and cloud-native technologies such as Redis, Kafka, Docker, Kubernetes, Hive, Spark, NSQ, or ZeroMQ.
- Hands-on experience with AI-related projects, including LLM application development, AI agent evaluation, model evaluation, AI-assisted testing, or AI testing frameworks.
- Experience leveraging AI tools (e.g. LLMs, AI coding assistants, or AI agents) to improve testing efficiency, automate test case generation, bug analysis, or software quality workflows.
Additional Information
- Posted: Sep 21, 2026