Cursor is actively hiring for 21 AI-related roles, with a significant focus on the "agents" stage, representing 52% of their open positions. The majority of these roles are within the Engineering function, and all current hiring is concentrated in the United States. Their technical needs are reflected in frequent tags such as agent_orchestration, llm_observability, and evals.
Currently tracking 15 active AI roles, up 30% versus the prior 4 weeks. Primary focus: Agent · Engineering.
Cursor currently has 25 active AI-related roles in our index. The most common open titles are: Data Scientist, Performance and Reliability, Engineering Manager, Core Services, Engineering Manager, Evals, Engineering Manager, Model Routing & Inference, Forward Deployed Engineer. Most positions are in Engineering and Product.
Cursor's active AI hiring is concentrated in: agents (44%), application (20%), evaluation (12%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Cursor is hiring AI talent in: United States (21 roles), United Kingdom (2 roles), Singapore (1 role).
Job postings at Cursor most frequently reference: agent orchestration, evals, llm observability, model serving, code gen.
In the past 30 days, Cursor has posted 5 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Engineering Manager, Evals Engineering Manager for the Evals team at Cursor, responsible for creating high-signal evaluation datasets for coding agents, building tools for engineers to write and run evals, and owning online evaluation systems that track agent quality in production. The role involves setting the eval roadmap, leading a team of engineers and researchers, guiding the development of evaluation benchmarks like CursorBench, defining online quality signals, and integrating evals into decision-making processes for launches, deploys, and model training. | Eval Gate | 8 |
| Software Engineer, Agent Evaluation and Quality Software Engineer on the Agent Quality team at Cursor, responsible for building the measurement, evaluation, and feedback-loop infrastructure to improve the Cursor core agent. This role involves designing and building AI evaluation systems, feedback loops from user usage, analysis tooling for agent behavior, and improving reliability and guardrails by making quality measurable. |
| Eval GateAgent |
| 8 |