Software Engineer, Agent Evaluation and Quality

Cursor; California (MO); On-site; USD 120,000 - 180,000; Full time

Job summary

Cursor is seeking a Software Engineer to join the Agent Quality team, building measurement, evaluation, and feedback-loop infrastructure that improves the core Cursor agent over time.

This role sits at the intersection of product, data, and engineering: instrumenting metrics, shaping quality definitions, and delivering pipelines to analyze agent behavior at scale. You will partner with research, product, and infrastructure to turn insights into improvements.

Qualifications

• Experience building AI evaluation or measurement systems (e.g., evals, experiments, ranking, or quality metrics).
• Strong data acumen with ability to collaborate with data scientists/researchers.
• Up-to-date with model/agent behavior research and industry trends.

Responsibilities

• Designing and building best-in-class AI evaluation system: curated datasets, offline replay, scorers/judges, regression alerts, dashboards.
• Designing feedback loops from real usage: collecting, cleaning, and interpreting user signals to inform model and harness changes.
• Developing analysis tooling and workflows for debugging agent behavior: deep dives on failure modes and clustering themes.
• Improving reliability and guardrails by making quality measurable and actionable: defining good/bad/degraded sessions, alerting, and triage primitives.

Skills

AI evals

Data analysis

Research collaboration

Production engineering

Tools

Python

Experimentation tooling

Job description

Our mission is to automate coding. The first step in our journey is to build the best tool for professional programmers, using a combination of inventive research, design, and engineering. Our organization is very flat, and our team is small and talent dense. We particularly like people who are truth-seeking, passionate, and creative. We enjoy spirited debate, crazy ideas, and shipping code.

About the Role

As a Software Engineer on the Agent Quality team at Cursor, you'll build the measurement, evaluation, and feedback-loop infrastructure that makes the Cursor core agent reliably better over time.

This role sits at the intersection of product, data, and engineering: you'll instrument what matters, help define how we judge quality, build pipelines and tooling to analyze agent behavior at scale, and partner closely with research, product, and infrastructure teams to turn insights into improvements.

Your impact will compound across every Cursor product built on the shared harness and across high-stakes decisions around model choice, quality, and cost.

What you'll work on

• Designing and building best-in-class AI evaluation system: curated datasets, offline replay, scorers / judges, regression alerts, and dashboards.

• Designing feedback loops from real usage: collecting, cleaning, and interpreting user signals to inform model and harness changes.

• Developing analysis tooling and workflows for debugging agent behavior: deep dives on failure modes, clustering themes, and surfacing actionable insights.

• Improving reliability and guardrails by making quality measurable and operational: defining "good/bad/degraded" sessions, alerting, and triage primitives.

You may be a fit if

• You've built and operated evaluation or measurement systems, such as AI evals, experimentation, ranking/relevance, or search quality. You can turn ambiguous "quality" questions into concrete metrics, pipelines, and decisions.

• You have strong data acumen, and can collaborate effectively with data scientists and researchers.

• You have taste and strong opinions on model and agent behaviors. You stay up-to-date and informed on emerging research and industry trends.

• You have strong software engineering fundamentals and enjoy shipping production systems.