Software Engineer, Bugbot

Cursor2 days ago

Location

SF / NY / Remote

Type

Full Time

Level

Mid

Role

Full Stack Engineer

Posted

Mar 12, 2026

Full TimeMid

The role

Summary

Cursor is seeking a full-stack Software Engineer to work on Bugbot, an AI-powered code review assistant that helps engineering teams ship higher-quality software. This role involves building end-to-end features, integrating LLMs into the development workflow, and ensuring the product maintains exceptional quality and reliability for millions of engineers.

What you'll do

End-to-end feature development: Launch new Bugbot features from concept to production, including UI design, backend implementation, and model behavior optimization

Review pipeline evolution: Adapt prompting strategies, model routing, context selection, and agent orchestration to leverage new AI capabilities

Integration development: Build seamless integrations that embed Bugbot into engineering workflows and development processes

Quality assurance and reliability: Monitor precision and recall metrics, triage false positives, and ensure consistent, trustworthy AI review output

User onboarding design: Create adoption flows that transition teams from installation to daily active usage of Bugbot

Cross-team collaboration: Partner with ML, infrastructure, and product teams to drive model improvements and scale system architecture

Product surface ownership: Own Bugbot's complete user experience including features, integrations, configuration, and AI code review interface

Performance optimization: Manage cost and latency while maintaining high-quality AI review capabilities

Customer feedback integration: Collect and implement feedback from both internal and external users to improve product quality

What we look for

Technical

Full-stack development experienceProven ability to ship product features end-to-end across frontend, backend, and system integration layers

AI/ML integration experienceExperience building or working with agents that integrate into code review or CI/CD workflows

Product development lifecycleExperience launching products or features to external users with full ownership of onboarding and iteration

Developer tooling backgroundUnderstanding of developer experience and familiarity with code review processes and workflows

Education

Computer Science degreeBachelor's degree in Computer Science, Software Engineering, or related technical field (or equivalent experience)

Technical portfolioStrong portfolio demonstrating full-stack development capabilities and AI integration experience

Experience

Full-stack product shippingDemonstrated experience moving fluidly between frontend, backend, and model integration layers

Customer-facing product launchExperience with external product launches including documentation, feedback collection, and iterative improvement

Quality-focused developmentAbility to balance rapid iteration with maintaining product trust and reliability

Collaborative developmentExperience working with cross-functional teams including ML, infrastructure, and product specialists

Skills

Required skills

Full-stack developmentProficiency in both frontend and backend technologies with ability to ship complete features

AI/ML integrationExperience integrating large language models and AI agents into production applications

Developer toolingDeep understanding of developer workflows, code review processes, and CI/CD integration

Product quality focusObsessive attention to quality with experience in evaluation metrics and user feedback integration

System designAbility to design scalable systems that handle model routing, context selection, and agent orchestration

Nice to have

Code review automationPrevious experience building or maintaining automated code review tools or systems

Developer experience optimizationTrack record of improving developer productivity through tooling and workflow enhancements

ML model evaluationExperience with precision/recall metrics and evaluation frameworks for AI systems

API integrationFamiliarity with GitHub, GitLab, or other version control platform APIs

Performance optimizationExperience optimizing cost and latency in AI-powered applications

Interview process

1
Initial screening — Phone or video call with recruiting team to discuss background and role fit
2
Technical phone screen — 45-minute technical interview focusing on full-stack development and system design concepts
3
Take-home project — Real-world coding challenge involving AI integration or developer tooling (3-4 hours)
4
Technical deep-dive — Review of take-home project with focus on architecture decisions and code quality
5
Product and culture fit — Discussion with team members about product vision, collaboration style, and company values
6
Final interview — Meeting with senior leadership to discuss career goals and long-term vision alignment