Fullstack Engineer (Data Application & AI Agent) - TikTok Live - Singapore

United States Digital Space LLC; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

Live in Singapore seeks a Fullstack Engineer to design, develop, and maintain data platform applications, APIs, and AI agent workflows across frontend, backend, and cloud services.

You will collaborate with product, data, AI, and infra teams to deliver high‑performance solutions and advance AI‑native development with LLMs and agents.

Qualifications

• Bachelor’s degree or above in Computer Science or a related technical discipline.
• Experience building modern web apps with a mainstream frontend framework (React/Vue/Angular).
• Experience creating backend services and APIs with distributed systems understanding.
• Familiar with frontend engineering, API design, and modern practices.
• Strong SQL/NoSQL data skills.
• Excellent written and spoken English for cross-functional collaboration.

Responsibilities

• Design, develop, and maintain full‑stack applications for LIVE Data Platform across frontend, backend, and APIs.
• Build intelligent data products such as analytics platforms, BI tools, and AI Agents.
• Collaborate with product, data, AI, and infrastructure teams to deliver scalable, reliable solutions.
• Explore AI‑native development using LLMs and AI Agents to enhance capabilities and user experience.
• Continuously improve engineering practices with reusable architecture, tooling, testing, and performance optimization.

Skills

React/Vue/Angular

Backend languages (Java/Go/Python/Node

Distributed systems

Frontend engineering & API design

SQL/NoSQL databases

English communication

Education

Bachelor's degree in Computer Science

Job description

Fullstack Engineer (Data Application & AI Agent) - the company Live - Singapore

Location: Singapore

Employment Type: Regular

Job Code: J2Y6L

Responsibilities

• Design, develop, and maintain full‑stack applications for the company LIVE Data Platform, including web applications, backend services, APIs, and AI‑native workflows.
• Build intelligent data products such as analytics platforms, diagnostic systems, BI tools, AI Agents, and data management platforms that improve business efficiency and decision making.
• Collaborate with product, data, AI, and infrastructure teams to deliver scalable, reliable, and high‑performance solutions across frontend, backend, and cloud services.
• Explore and adopt modern AI‑native development paradigms, leveraging LLMs and AI Agents to enhance product capabilities, engineering productivity, and user experience.
• Continuously improve engineering excellence through reusable architecture, developer tooling, testing, performance optimization, and best practices.

Minimum Qualifications

• Bachelor’s degree or above in Computer Science or a related technical discipline.
• Solid software engineering fundamentals with experience developing modern web applications using at least one mainstream frontend framework (React, Vue, Angular, etc.).
• Experience building backend services and APIs with at least one backend language (Java, Go, Python, Node.js, etc.), with understanding of distributed systems and service‑oriented architecture.
• Familiar with frontend engineering, component‑based development, API design, and modern software development practices.
• Good understanding of databases, data modeling, and common storage technologies (SQL/NoSQL).
• Strong problem‑solving ability, communication skills, and willingness to learn new technologies in a fast‑paced environment.
• Good written and spoken English for cross‑functional and cross‑regional collaboration.

Preferred Qualifications

• Experience building data platforms, data infrastructure, or data‑intensive applications, with familiarity in technologies such as Spark, Flink, Kafka, ClickHouse, Doris, Elasticsearch, or similar systems.
• Experience developing data visualization platforms, BI systems, dashboards, or analytical applications using modern visualization frameworks.
• Hands‑on experience building AI‑native applications or AI Agents, with practical knowledge of Agent architectures, orchestration frameworks, tool calling, memory, planning, and evaluation methodologies.