Software Engineer, RL Data

Cursor

San Francisco, CA

On-site

Who this role is best for

Strong fit for software engineers with infra or data background who enjoy turning messy agent behavior into structured datasets, working in a small, flat team in San Francisco.

Best fit for

Software engineers with experience in infra, data, or distributed systems and a passion for creating training environments for AI agents
— “You have an infra, data, or distributed systems background.”
Candidates who thrive on iterative development and refining tasks based on model performance feedback
— “Designing a task set that teaches a specific agent capability, then iterating on it from traces and evals until the model actually gets better.”

Things to consider

The position emphasizes working in a small, talent-dense team, which may require high autonomy and adaptability.
— “Our team is small and talent dense.”

How to stand out

Emphasize your ability to structure abstract capabilities into measurable tasks in your resume and interviews
— “You like setting tasks: breaking a fuzzy capability into something concrete you can measure.”
Highlight projects where you turned complex or messy data into reusable systems or tools
— “Turning a one-off recipe into something other teams can reuse: better rewards, cleaner environments, tighter data quality.”
Demonstrate your experience in analyzing system behavior and extracting actionable insights
— “Reading a pile of agent traces, finding a failure mode or a surprising behavior, and building a system that surfaces more of the same.”

Pace · SteadyCollaboration · MediumAutonomy · MediumDecision Impact · Individual

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

designing a task set that teaches a specific agent capability
iterating on task set from traces and evals
turning a one-off recipe into something reusable

Typical background

background in infrastructure, data, or distributed systems

Skills & requirements

Required

Software Engineering FundamentalsCareful And Fast CodeSetting TasksInfrastructure, Data, Or Distributed Systems Background

Preferred

RL Experience

Stack & domain

PythonKotlinAWSMySQLKubernetesDistributed SystemsReinforcement LearningProblem-solvingTeamworkCommunicationCodingData EngineeringMachine Learning

About the role

Original posting from Cursor via Ashby

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.
SOFTWARE ENGINEER, REINFORCEMENT LEARNING
Cursor is building the future of coding. We train frontier coding agents https://cursor.com/blog/composer and scale RL on real user data to make them increasingly effective.
ABOUT THE ROLE
As a Software Engineer on the RL Data team at Cursor, you'll create the tasks, rewards, and environments that train our coding agents. The team owns the data that goes into training: what the model is asked to do, how we score it, and the setups it learns in.
WHAT YOU’LL DO
Designing a task set that teaches a specific agent capability, then iterating on it from traces and evals until the model actually gets better.
Reading a pile of agent traces, finding a failure mode or a surprising behavior, and building a system that surfaces more of the same.
Turning a one-off recipe into something other teams can reuse: better rewards, cleaner environments, tighter data quality.
Partnering with research on whether a dataset is actually teaching the thing we think it is.
YOU MAY BE A FIT IF
You write careful, fast code and have strong software engineering fundamentals.
You like setting tasks: breaking a fuzzy capability into something concrete you can measure.
You have an infra, data, or distributed systems background. RL experience is a plus, not a requirement.
You enjoy looking at messy real-world agent behavior and turning it into a dataset or a tool.

Source: Cursor careers (Ashby)