Frontend Infrastructure Engineer (AI Tooling), TikTok Client Arch

TikTok's Web Architecture team is looking for a visionary Frontend Infrastructure Engineer (AI Tooling) to shape the future of AI-driven frontend engineering. You will work on the evolution of our monorepo toolchain, web application architecture and frameworks, while integrating LLM-powered automation and intelligent development workflows to build an AI-native frontend infrastructure.

Key Responsibilities:

• Define and prototype what "AI-native frontend infrastructure" means in practice - where both humans and AI agents are first-class users of the development platform and tooling.
• Transform frontend developer experience by leveraging AI to automate and enhance repository maintenance, large-scale refactoring, error diagnosis and remediation, CI/CD automation, and knowledge management across complex codebases.
• Establish evaluation and benchmarking frameworks to measure AI-assisted engineering productivity, reliability, and code correctness at scale.
• Design and build AI-native interaction paradigms, web application architectures, and supporting frameworks that enable AI-driven user experiences.
• Stay abreast of the latest web technologies, trends, and industry practices. Evaluate and recommend new tools, frameworks, and methodologies to enhance the team's efficiency.
• Partner with engineering teams and cross-functional teams to identify challenges, deliver scalable platform solutions, and drive adoption with measurable impact. Minimum Qualification(s):
• Experience: extensive web development experience, with a strong focus on frontend infrastructure
• Strong expertise in modern web technologies, including HTML, CSS, JavaScript/TypeScript, and at least one major frontend framework (e.g., React or Vue).
• Deep experience with large-scale frontend infrastructure, including monorepo toolchains (e.g., Rush, pnpm, Turborepo), dependency management, CI/CD pipelines, and incremental build systems.
• Demonstrated experience architecting complex frontend or platform systems, including the design of reusable development frameworks, extensible abstractions, and scalable engineering standards.
• Experience integrating LLMs or AI systems into engineering workflows (e.g., code generation, refactoring tools, automated code review, CI automation).
• Strong system-level problem-solving ability, with experience navigating large codebases and driving architectural evolution.
• Ability to influence technical direction and collaborate across teams to drive platform adoption at scale.

Preferred Qualification(s):

• Track record in successful AI application development and adoption.
• Experience building developer platforms, internal tooling systems, or engineering productivity infrastructure.
• Strong learning ability and interest in exploring how AI can reshape developer productivity and engineering infrastructure.
• Prior experience in a technology-driven startup or fast-paced environment.