Job description

The TikTok General Architecture team sits between business and infrastructure. Our mission is to embrace AI, build the most advanced business architecture infrastructure, establish public trust and compliance, focus on resource management and cost optimization, user experience and stability, improve engineering quality and R&D efficiency. Here, you can both feel how technology empowers upper-layer business and deepen your technical understanding at the architecture level. We look forward to your joining! We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. Responsibilities - Explore and implement "AI-Native Engineering Infrastructure", treating AI Agents and human developers as first-class citizens of the platform and redefining R&D efficiency. - Leverage AI to drive automated maintenance, intelligent refactoring, precise diagnosis/repair, CI/CD optimization, and knowledge management across large codebases—transforming the development experience. - Establish and continuously improve evaluation standards and benchmarking for AI-assisted R&D efficiency, measuring productivity, system stability, and code correctness. - Design and build application architectures, service interfaces, and supporting frameworks for AI-driven scenarios, providing a solid foundation for upper-layer innovation. - Stay current with software engineering and systems technologies; evaluate and adopt new tools, frameworks, and methodologies to evolve the team's stack. - Partner with business R&D and cross-functional teams to understand pain points, deliver highly available platform solutions at scale, and drive adoption with measurable impact. Minimum Qualifications - Individuals who are completing or have recently completed a Bachelor's degree in computer science or a related discipline. - Hands-on software development experience (coursework, internship, open source, or personal projects); able to independently implement, debug, and deliver features. - End-to-end delivery mindset: hands-on practice in at least two of client/application, server, and data layers, with basic understanding of the rest. - Basic system design ability: decompose and model small-to-medium systems; articulate module boundaries, data flow, critical paths, and key trade-offs (performance, complexity, scalability, etc.). - Understanding of engineering basics (build, dependency management, CI/CD, automation, or deployment), with interest in engineering/infrastructure work. - Strong problem-solving and code-reading skills; able to navigate unfamiliar codebases and deliver improvements. Clear communication and collaboration. - Interest in or early practice with AI-assisted engineering, and motivation to apply AI in real engineering scenarios. Preferred Qualifications - Project or internship experience building AI applications/agents, or integrating LLMs into developer workflows. - Experience with engineering productivity, internal tools, developer platforms, or R&D efficiency projects (internship, open source, or coursework). - Hands-on exposure to CI/CD, build & deployment, automation, or observability tooling, with awareness of design trade-offs. - Internship experience in full-stack, client, or server-side roles at Internet companies or technology-driven teams. - Independent understanding of software architecture and system design, with a strong willingness to keep learning. - Technical writing, open-source contributions, talks, or clear explanation of design trade-offs. - Deeper project experience in Web, mobile, backend services, data, or infrastructure (a plus, not a requirement).

Requirements

Must-haves

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.
Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.
Explore and implement "AI-Native Engineering Infrastructure", treating AI Agents and human developers as first-class citizens of the platform and redefining R&D efficiency.
Leverage AI to drive automated maintenance, intelligent refactoring, precise diagnosis/repair, CI/CD optimization, and knowledge management across large codebases—transforming the development experience.
Establish and continuously improve evaluation standards and benchmarking for AI-assisted R&D efficiency, measuring productivity, system stability, and code correctness.
Design and build application architectures, service interfaces, and supporting frameworks for AI-driven scenarios, providing a solid foundation for upper-layer innovation.
Stay current with software engineering and systems technologies; evaluate and adopt new tools, frameworks, and methodologies to evolve the team's stack.
Partner with business R&D and cross-functional teams to understand pain points, deliver highly available platform solutions at scale, and drive adoption with measurable impact.
Individuals who are completing or have recently completed a Bachelor's degree in computer science or a related discipline.
Hands-on software development experience (coursework, internship, open source, or personal projects); able to independently implement, debug, and deliver features.
End-to-end delivery mindset: hands-on practice in at least two of client/application, server, and data layers, with basic understanding of the rest.
Basic system design ability: decompose and model small-to-medium systems; articulate module boundaries, data flow, critical paths, and key trade-offs (performance, complexity, scalability, etc.).
Understanding of engineering basics (build, dependency management, CI/CD, automation, or deployment), with interest in engineering/infrastructure work.
Strong problem-solving and code-reading skills; able to navigate unfamiliar codebases and deliver improvements. Clear communication and collaboration.
Interest in or early practice with AI-assisted engineering, and motivation to apply AI in real engineering scenarios.

Nice-to-haves

Project or internship experience building AI applications/agents, or integrating LLMs into developer workflows.
Experience with engineering productivity, internal tools, developer platforms, or R&D efficiency projects (internship, open source, or coursework).
Hands-on exposure to CI/CD, build & deployment, automation, or observability tooling, with awareness of design trade-offs.
Internship experience in full-stack, client, or server-side roles at Internet companies or technology-driven teams.
Independent understanding of software architecture and system design, with a strong willingness to keep learning.
Technical writing, open-source contributions, talks, or clear explanation of design trade-offs.
Deeper project experience in Web, mobile, backend services, data, or infrastructure (a plus, not a requirement).

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aici/cdrest

Platform: tiktok
Effort: medium