New role emerges: from evaluation to channel collaboration
Further industry segmentation has created demand for compound talents combining "evaluation and channel" skills. Since large model deployment often relies on AI channel agents or token proxy services, capability comparison specialists need to collaborate with these partners to ensure the evaluation environment is consistent with the client's actual call chain. For example, a company's job posting states: "Must be familiar with mainstream AI large model agent platforms, able to assess whether model versions provided by different agents are consistent with the official version." Meanwhile, some companies have started building internal token relay stations to isolate evaluation and production traffic, which also requires evaluators to understand distributed inference architectures. It is foreseeable that as benchmark chaos persists, capability comparison specialists will evolve from temporary positions to standard configurations in enterprise AI teams, with their salary levels already approaching those of senior architects. For job seekers, mastering cross-model evaluation methodologies and having token cost sensitivity will become the most sought-after skill set by the end of 2026.