Backend Software Engineer - TikTok Live (Data Platform) - Singapore
May 26, 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: 10,000+ employees
- Industry: Technology: Consumer Internet
Why you should apply for a job to TikTok:
4.5/5 in overall job satisfaction
4.5/5 in supportive management
100% say women are treated fairly and equally to men
100% would recommend this company to other women
100% say the CEO supports gender diversity
Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›
Responsibilities
With the enormous growth of live streaming, TikTok LIVE aims to inspire real-time interactions and help creators connect with audiences around the world.
TikTok LIVE Data Platform builds the data and AI infrastructure that supports product experience, business operations, and internal decision making across LIVE. Our work covers the Index Platform, Label Platform, Portrait Platform, Diagnostic Platform, Data Asset Management Platform, Data Suite, Data Agent, and AI-native data solutions for internal and business users.
The platform serves data applications across TikTok LIVE, including data processing, OLAP analytics, data visualization, intelligent diagnostics, and AI-powered analytics workflows. The backend systems involve large-scale streaming processing, offline pipelines, OLAP storage such as ClickHouse and Doris, KV storage, data APIs, and high-performance services that power user-facing products and internal platforms such as agency backstage systems.
We are looking for passionate backend engineers to design and build reliable, scalable, and high-performance distributed systems. You will work closely with product managers, data engineers, AI engineers, and infrastructure teams to deliver data products that turn complex data into actionable insights and enable the next generation of AI-native data applications.
Responsibilities:
- Design, develop, and maintain backend services, data APIs, and distributed systems for TikTok LIVE Data Platform.
- Build and optimize large-scale data products, including analytics platforms, diagnostic systems, BI tools, data asset management systems, and Data Agent capabilities.
- Develop robust and efficient backend architecture for real-time and offline data processing, OLAP analytics, data services, and internal business applications.
- Explore and apply AI-native engineering practices, including LLM-powered analytics, intelligent diagnostics, agent workflows, tool calling, and automation, to improve product capability and engineering productivity.
- Plan and lead technical projects that support the iterative development and scaling of early-stage and high-impact products.
- Collaborate with cross-functional teams to translate product and business requirements into scalable technical solutions.
- Contribute to engineering strategy, system reliability, developer tooling, testing, performance optimization, and team culture.
Qualifications
Minimum Qualifications:
- Bachelor's degree or above in Computer Science or a related technical discipline.
- Strong software engineering fundamentals, including solid understanding of computer architecture, data structures, algorithms, and system design.
- Experience building scalable, highly available, distributed, and mission-critical backend systems.
- Hands-on experience with at least one backend programming language such as Go, Java, Python, or C++.
- Good understanding of databases, data modeling, storage systems, and service-oriented architecture.
- Strong problem-solving ability, ownership, communication skills, and willingness to learn in a fast-paced environment.
- Able to work closely with product, data, AI, infrastructure, and business stakeholders across regions.
Preferred Qualification:
- 3 years or more of relevant backend engineering experience in a large-scale internet business.
- Experience building data platforms, data infrastructure, or data-intensive applications, with familiarity in systems such as Spark, Flink, Kafka, ClickHouse, Doris, Elasticsearch, or similar technologies.
- Experience with real-time data processing, offline pipelines, OLAP analytics, high-concurrency services, or large-scale distributed storage systems.
- Hands-on experience building AI-native applications or AI Agents, with practical knowledge of agent architecture, orchestration, tool calling, memory, planning, or evaluation methodologies.
With the enormous growth of live streaming, TikTok LIVE aims to inspire real-time interactions and help creators connect with audiences around the world.
TikTok LIVE Data Platform builds the data and AI infrastructure that supports product experience, business operations, and internal decision making across LIVE. Our work covers the Index Platform, Label Platform, Portrait Platform, Diagnostic Platform, Data Asset Management Platform, Data Suite, Data Agent, and AI-native data solutions for internal and business users.
The platform serves data applications across TikTok LIVE, including data processing, OLAP analytics, data visualization, intelligent diagnostics, and AI-powered analytics workflows. The backend systems involve large-scale streaming processing, offline pipelines, OLAP storage such as ClickHouse and Doris, KV storage, data APIs, and high-performance services that power user-facing products and internal platforms such as agency backstage systems.
We are looking for passionate backend engineers to design and build reliable, scalable, and high-performance distributed systems. You will work closely with product managers, data engineers, AI engineers, and infrastructure teams to deliver data products that turn complex data into actionable insights and enable the next generation of AI-native data applications.
Responsibilities:
- Design, develop, and maintain backend services, data APIs, and distributed systems for TikTok LIVE Data Platform.
- Build and optimize large-scale data products, including analytics platforms, diagnostic systems, BI tools, data asset management systems, and Data Agent capabilities.
- Develop robust and efficient backend architecture for real-time and offline data processing, OLAP analytics, data services, and internal business applications.
- Explore and apply AI-native engineering practices, including LLM-powered analytics, intelligent diagnostics, agent workflows, tool calling, and automation, to improve product capability and engineering productivity.
- Plan and lead technical projects that support the iterative development and scaling of early-stage and high-impact products.
- Collaborate with cross-functional teams to translate product and business requirements into scalable technical solutions.
- Contribute to engineering strategy, system reliability, developer tooling, testing, performance optimization, and team culture.
Minimum Qualifications:
- Bachelor's degree or above in Computer Science or a related technical discipline.
- Strong software engineering fundamentals, including solid understanding of computer architecture, data structures, algorithms, and system design.
- Experience building scalable, highly available, distributed, and mission-critical backend systems.
- Hands-on experience with at least one backend programming language such as Go, Java, Python, or C++.
- Good understanding of databases, data modeling, storage systems, and service-oriented architecture.
- Strong problem-solving ability, ownership, communication skills, and willingness to learn in a fast-paced environment.
- Able to work closely with product, data, AI, infrastructure, and business stakeholders across regions.
Preferred Qualification:
- 3 years or more of relevant backend engineering experience in a large-scale internet business.
- Experience building data platforms, data infrastructure, or data-intensive applications, with familiarity in systems such as Spark, Flink, Kafka, ClickHouse, Doris, Elasticsearch, or similar technologies.
- Experience with real-time data processing, offline pipelines, OLAP analytics, high-concurrency services, or large-scale distributed storage systems.
- Hands-on experience building AI-native applications or AI Agents, with practical knowledge of agent architecture, orchestration, tool calling, memory, planning, or evaluation methodologies.
With the enormous growth of live streaming, TikTok LIVE aims to inspire real-time interactions and help creators connect with audiences around the world.
TikTok LIVE Data Platform builds the data and AI infrastructure that supports product experience, business operations, and internal decision making across LIVE. Our work covers the Index Platform, Label Platform, Portrait Platform, Diagnostic Platform, Data Asset Management Platform, Data Suite, Data Agent, and AI-native data solutions for internal and business users.
The platform serves data applications across TikTok LIVE, including data processing, OLAP analytics, data visualization, intelligent diagnostics, and AI-powered analytics workflows. The backend systems involve large-scale streaming processing, offline pipelines, OLAP storage such as ClickHouse and Doris, KV storage, data APIs, and high-performance services that power user-facing products and internal platforms such as agency backstage systems.
We are looking for passionate backend engineers to design and build reliable, scalable, and high-performance distributed systems. You will work closely with product managers, data engineers, AI engineers, and infrastructure teams to deliver data products that turn complex data into actionable insights and enable the next generation of AI-native data applications.
Responsibilities:
- Design, develop, and maintain backend services, data APIs, and distributed systems for TikTok LIVE Data Platform.
- Build and optimize large-scale data products, including analytics platforms, diagnostic systems, BI tools, data asset management systems, and Data Agent capabilities.
- Develop robust and efficient backend architecture for real-time and offline data processing, OLAP analytics, data services, and internal business applications.
- Explore and apply AI-native engineering practices, including LLM-powered analytics, intelligent diagnostics, agent workflows, tool calling, and automation, to improve product capability and engineering productivity.
- Plan and lead technical projects that support the iterative development and scaling of early-stage and high-impact products.
- Collaborate with cross-functional teams to translate product and business requirements into scalable technical solutions.
- Contribute to engineering strategy, system reliability, developer tooling, testing, performance optimization, and team culture.
Qualifications
Minimum Qualifications:
- Bachelor's degree or above in Computer Science or a related technical discipline.
- Strong software engineering fundamentals, including solid understanding of computer architecture, data structures, algorithms, and system design.
- Experience building scalable, highly available, distributed, and mission-critical backend systems.
- Hands-on experience with at least one backend programming language such as Go, Java, Python, or C++.
- Good understanding of databases, data modeling, storage systems, and service-oriented architecture.
- Strong problem-solving ability, ownership, communication skills, and willingness to learn in a fast-paced environment.
- Able to work closely with product, data, AI, infrastructure, and business stakeholders across regions.
Preferred Qualification:
- 3 years or more of relevant backend engineering experience in a large-scale internet business.
- Experience building data platforms, data infrastructure, or data-intensive applications, with familiarity in systems such as Spark, Flink, Kafka, ClickHouse, Doris, Elasticsearch, or similar technologies.
- Experience with real-time data processing, offline pipelines, OLAP analytics, high-concurrency services, or large-scale distributed storage systems.
- Hands-on experience building AI-native applications or AI Agents, with practical knowledge of agent architecture, orchestration, tool calling, memory, planning, or evaluation methodologies.
Responsibilities
ResponsibilitiesWith the enormous growth of live streaming, TikTok LIVE aims to inspire real-time interactions and help creators connect with audiences around the world.
TikTok LIVE Data Platform builds the data and AI infrastructure that supports product experience, business operations, and internal decision making across LIVE. Our work covers the Index Platform, Label Platform, Portrait Platform, Diagnostic Platform, Data Asset Management Platform, Data Suite, Data Agent, and AI-native data solutions for internal and business users.
The platform serves data applications across TikTok LIVE, including data processing, OLAP analytics, data visualization, intelligent diagnostics, and AI-powered analytics workflows. The backend systems involve large-scale streaming processing, offline pipelines, OLAP storage such as ClickHouse and Doris, KV storage, data APIs, and high-performance services that power user-facing products and internal platforms such as agency backstage systems.
We are looking for passionate backend engineers to design and build reliable, scalable, and high-performance distributed systems. You will work closely with product managers, data engineers, AI engineers, and infrastructure teams to deliver data products that turn complex data into actionable insights and enable the next generation of AI-native data applications.
Responsibilities:
- Design, develop, and maintain backend services, data APIs, and distributed systems for TikTok LIVE Data Platform.
- Build and optimize large-scale data products, including analytics platforms, diagnostic systems, BI tools, data asset management systems, and Data Agent capabilities.
- Develop robust and efficient backend architecture for real-time and offline data processing, OLAP analytics, data services, and internal business applications.
- Explore and apply AI-native engineering practices, including LLM-powered analytics, intelligent diagnostics, agent workflows, tool calling, and automation, to improve product capability and engineering productivity.
- Plan and lead technical projects that support the iterative development and scaling of early-stage and high-impact products.
- Collaborate with cross-functional teams to translate product and business requirements into scalable technical solutions.
- Contribute to engineering strategy, system reliability, developer tooling, testing, performance optimization, and team culture.
Qualifications
QualificationsMinimum Qualifications:
- Bachelor's degree or above in Computer Science or a related technical discipline.
- Strong software engineering fundamentals, including solid understanding of computer architecture, data structures, algorithms, and system design.
- Experience building scalable, highly available, distributed, and mission-critical backend systems.
- Hands-on experience with at least one backend programming language such as Go, Java, Python, or C++.
- Good understanding of databases, data modeling, storage systems, and service-oriented architecture.
- Strong problem-solving ability, ownership, communication skills, and willingness to learn in a fast-paced environment.
- Able to work closely with product, data, AI, infrastructure, and business stakeholders across regions.
Preferred Qualification:
- 3 years or more of relevant backend engineering experience in a large-scale internet business.
- Experience building data platforms, data infrastructure, or data-intensive applications, with familiarity in systems such as Spark, Flink, Kafka, ClickHouse, Doris, Elasticsearch, or similar technologies.
- Experience with real-time data processing, offline pipelines, OLAP analytics, high-concurrency services, or large-scale distributed storage systems.
- Hands-on experience building AI-native applications or AI Agents, with practical knowledge of agent architecture, orchestration, tool calling, memory, planning, or evaluation methodologies.
Additional Information
- Posted: May 26, 2026