# Software Engineer, Agent Evaluation and Quality
**Company:** [Cursor](https://scaleengineer.com/companies/cursor)
Cursor is seeking a Software Engineer for their Agent Evaluation and Quality team to build cutting-edge AI evaluation infrastructure. The ideal candidate will design measurement systems, develop feedback loops, and create tooling to improve AI agent reliability and performance across the company's product ecosystem.
**Role:** Software Engineer
**Seniority:** Senior
**Locations:** San Francisco
**Salary:** 180000–250000 USD
[Apply](https://jobs.ashbyhq.com/cursor/2bbe9f02-83a5-4173-98be-9085d1cb5693)
Canonical: https://scaleengineer.com/jobs/cursor/software-engineer-agent-evaluation-and-quality
---
## Responsibilities

- AI Evaluation System Design: Create comprehensive AI evaluation systems including curated datasets, offline replay mechanisms, scoring frameworks, regression alerts, and performance dashboards.
- Feedback Loop Development: Design and implement robust feedback collection mechanisms to gather, clean, and interpret user signals that inform model and system improvements.
- Analysis Tooling: Develop advanced debugging and analysis workflows to identify agent behavior patterns, investigate failure modes, and surface actionable insights.
- Quality Measurement: Establish operational quality metrics, define performance thresholds, create alerting mechanisms, and develop triage strategies for AI agent reliability.

## Requirements

### education

- {"name":"Computer Science","description":"Bachelor's or Master's degree in Computer Science, Software Engineering, or related technical field preferred"}

### technical

- {"name":"AI Evaluation Systems","description":"Proven experience in building and operating evaluation systems for AI, experimentation platforms, ranking/relevance, or search quality metrics"}
- {"name":"Data Analysis","description":"Strong data analysis skills with ability to transform abstract quality concepts into concrete metrics and decision-making pipelines"}
- {"name":"Software Engineering","description":"Solid software engineering fundamentals with expertise in building and shipping robust production systems"}

### experience

- {"name":"AI/ML Systems","description":"Demonstrated experience working with AI and machine learning evaluation frameworks"}
- {"name":"Production Systems","description":"Track record of developing and maintaining large-scale software infrastructure"}

## Skills

### required

- {"name":"AI Evaluation","description":"Expertise in designing comprehensive AI quality measurement systems"}
- {"name":"Data Pipeline Development","description":"Ability to create robust data collection and processing pipelines"}
- {"name":"System Design","description":"Strong skills in designing scalable and reliable software infrastructure"}

### preferred

- {"name":"Machine Learning Research","description":"Familiarity with latest AI research trends and emerging technologies"}
- {"name":"Distributed Systems","description":"Experience with large-scale distributed computing architectures"}

## Tech stack

### tools

- {"name":"Data Analysis Tools","description":"Proficiency in Jupyter, pandas, and advanced data visualization libraries"}

### others

- {"name":"Cloud Platforms","description":"Experience with cloud infrastructure for scalable AI systems"}

### databases

- {"name":"Time Series Databases","description":"Databases for storing and analyzing performance metrics and evaluation data"}

### languages

- {"name":"Python","description":"Primary programming language for data analysis and AI system development"}

### frameworks

- {"name":"Machine Learning Frameworks","description":"Experience with TensorFlow, PyTorch, or similar AI/ML frameworks"}

## Benefits

### benefits

- {"name":"Health Insurance","description":"Comprehensive medical, dental, and vision coverage"}
- {"name":"Equity","description":"Competitive stock option package for early-stage startup"}
- {"name":"Professional Development","description":"Continuous learning opportunities and conference attendance support"}

## Compensation

- **max:** 250000
- **min:** 180000
- **currency:** USD
- **stockOptions:** true

## Interview process

### steps

- {"name":"Initial Screening","description":"Brief introductory call to assess initial fit and background"}
- {"name":"Technical Interviews","description":"2-3 focused technical interviews exploring problem-solving and technical expertise"}
- {"name":"Onsite Project","description":"In-office project where candidates work on a small technical challenge and meet the team"}

## Full 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.

## Applying

If there appears to be a fit, we'll reach to schedule 2-3 short technicals. After, we'll schedule an onsite in our office, where you'll work on a small project, discuss ideas, and meet the team.

#LI-DNI