Software Engineer, AI Data Application – USDS

About the Team

The TikTok U.S. Data Security (USDS) team is responsible for the security, integrity, and compliance of TikTok’s data within the United States. The Data Platform Team builds a scalable, reliable, cost-efficient infrastructure that ensures data integrity and empowers every business unit to win through self-service tools and scientific insights.

We are seeking a Software Engineer to help improve company-wide efficiency and self-service capabilities through AI-driven innovation. In this role, you will contribute to internal products that automate manual workflows, improve data accessibility, and help business and engineering teams work more efficiently.

Responsibilities

• Design, build, and maintain backend services and internal platform components with guidance from senior engineers, focusing on reliability, maintainability, and performance.
• Develop backend capabilities for AI-powered products, including data services, workflow orchestration, model integration, and intelligent automation, while following established engineering and safety practices.
• Work with product, engineering, and data stakeholders to understand team pain points and contribute reusable APIs, backend components, and self-service tools that reduce manual work.
• Apply best practices in service architecture, API design, observability, testing, and operational excellence, and help improve team standards through day-to-day implementation.
• Collaborate closely with software/fullstack engineers, data scientists, and business stakeholders to translate requirements into practical backend solutions.

Minimum Qualifications

• Education: BS/MS in Computer Science, Engineering, or a related technical field.
• Experience: 3+ years of software development experience, with hands-on experience building and maintaining backend systems or platform services in production environments.
• Backend Proficiency: Proficiency in backend languages and frameworks such as Python, Go, Java, or Node.js, with experience building APIs, services, and integrations.
• Data & Infrastructure Foundations: Working knowledge of databases, caching, messaging systems, and cloud-native infrastructure; comfortable contributing to systems designed for scalability, resilience, and operational efficiency.

Preferred Qualifications

• AI Systems Experience: Experience integrating LLM APIs, RAG pipelines, model-serving infrastructure, or agentic workflows into backend systems, with an interest in reliability, safety, and production readiness.
• Internal Platform Experience: Experience contributing to internal platforms, service frameworks, workflow engines, developer tools, or data infrastructure used by engineering or business teams.
• System Design Strength: Ability to design clear, maintainable components and participate in technical design discussions, considering performance, complexity, and developer experience.