Senior Software Engineer, Enterprise Platform - Frontier Generative AI

We're a high-ownership engineering team inside TikTok USDS JV shipping a flagship B2B AI product at the frontier of large-model inference and creative automation. If you want your engineering decisions to be the reason an industry-leading brand team trusts a new AI platform with their content production, this is the seat.

About the Team

We are the engineering incubator for TikTok USDS JV's newest enterprise AI products. Our remit spans the full lifecycle — from the first localizable prototype to a scaled, multi-region, enterprise-grade service. The team has shipped products that have grown from a handful of design partners to global enterprise rollouts, and the pipeline keeps growing.

We operate with a strong 0→1 mindset: ambiguity is the default, ownership is non-negotiable, and the patterns that the next decade of enterprise AI will be measured against are being prototyped on our team right now.

Responsibilities

• End-to-end product engineering. Take ideas from prototype to production. One week you might be building the foundational services that power the product; the next, the user-facing surface or operator tooling; the week after, the instrumentation and feedback loops that tell you whether it worked.
• Enterprise features with real customer impact. Ship the capabilities enterprise customers evaluate, contract against, and renew on — features that have to meet a real-world quality bar, not a demo bar.
• Pair with ML on the frontier. Work side by side with our ML and inference teams to turn frontier model capability into something enterprise customers can rely on — predictable, isolated, audit-ready, and built for the kind of scale only a frontier AI product sees.

Minimum Qualifications

• BS or MS in Computer Science, Computer Engineering, or a related technical discipline, with industry experience.
• 3+ years as a software engineer, with proven contributions to team-based, production systems — ideally in a collaborative, multi-disciplinary environment.
• Solid programming skills in C/C++ and/or Python, with a strong grasp of data structures and algorithms.
• Comfort moving across the stack — backend services, user-facing surfaces, instrumentation and tooling — and the engineering rigor to know which trade-offs matter at which layer.
• Strong sense of ownership and a bias for action: you finish what you start, and you ship.

Preferred Qualifications

• End-to-end product engineering experience; B2B or enterprise platform experience;
• Hands-on or adjacent experience with ML systems, GPU serving, or other compute-intensive AI workloads; distributed systems, concurrent programming, and Microservices.