Senior Product Manager - Corporate Information Systems - AI Vertical Team

Team Introduction We are the AI Vertical Scenarios Team under the Corporate Information Systems department. Our core mission is to serve ByteDance's global internal office scenarios as the standard-setter for AI-native applications and the driver of globally consistent experiences — we both build flagship AI application scenarios in-house and, using a full-scope evaluation suite as our measurement foundation, drive functional and experiential parity between CN and non-CN regions across core scenarios. Every feature you ship here is backed by the real, everyday usage and feedback of ByteDance employees worldwide. Here, you'll be deeply involved in the entire journey of an enterprise AI product — from idea to launch!

Responsibilities

1. Lead evaluation product planning and system design: for core scenarios such as AI Agents and Coding Agents, design the evaluation framework, workflow, and product mechanisms, turning frontier capabilities into reusable and continuously evolving evaluation systems;
2. Uncover the real needs of enterprise users: distill users' core pain points through interviews, data analysis, and behavioral insights, and drive them into the product;
3. Drive evaluation engineering and cross-functional collaboration: work closely with algorithm, engineering, and data teams to build evaluation platforms, automated pipelines, and result dashboards so evaluation can directly support model optimization and product decisions.

Qualifications Minimum Qualifications

• Bachelor's degree or above; backgrounds in Computer Science, Artificial Intelligence, Information Management, Statistics, or related fields；
• Solid structured thinking and sustained interest at the intersection of evaluation, data, and AI products are important;
• Clear logical thinking, self-driven, and user-value oriented; able to think from the user's perspective to solve problems, with strong communication and cross-team collaboration skills;
• Genuine interest in AI products, model evaluation, and benchmark systems, with a habit of following the latest developments in the LLM / Agent space;
• Familiar with AI / Agent tools such as Claude Code, Cursor, Codex.

Preferred Qualifications

• Experience using, analyzing, or building around third-party benchmarks such as SWE-Bench is a plus;
• Understanding of evaluation automation, data processing, or experiment pipelines is preferred; hands-on experience building agents, evaluation platforms, or AI applications is a plus.