Job Description

About the team

Our team supports platform behind TikTok’s AIGC and effects submission pipelines. We develop and operate the tools and workflow runtime that internal creators, effect designers, and AI/ML teams use to compose, monitor, and debug complex AI workflows — from model inference chains to asset processing and publishing.

As a Software Engineer, you will own full‑stack features in our workflow related services. You’ll work closely with product managers, designers, and AI/ML engineers to turn ambiguous creator and platform needs into reliable tools that make shipping AI‑powered effects project fast, safe, and enjoyable.

Responsibilities

- Own end‑to‑end development of key features in our workflow editor and related services – from problem discovery and design, to implementation, rollout, and long‑term maintenance.

- Design and build full‑stack product experiences for the editor, including rich graph‑based UI (React/TypeScript or similar) and backend services (Go or equivalent) that orchestrate workflow execution, scheduling, and state management.

- Collaborate with AI/ML platform teams to integrate models and pipelines (e.g., LLMs, diffusion, vision models) into reusable workflow nodes, with clear contracts, versioning, and observability.

- Build internal tooling for debugging and operating workflows: run history, logs & metrics, replay, tracing, and guardrail/safety controls surfaced in the editor.

- Partner with product and data/ML teams to design experiments and evaluation flows around workflows (e.g., offline metrics, staged rollout, A/B experiments) and fold the results back into product decisions.

- Improve the reliability, performance, and usability of the editor and backend services through systematic instrumentation, alerting, on‑call participation, and regular post‑mortems.

- Work closely with designers to refine interaction patterns for complex graph editing, parameter configuration, and status visualization, balancing power and simplicity.

- Contribute to the overall roadmap of the workflow platform, identifying reusable abstractions and collaborating with other teams that depend on workflow capabilities.