Generalist Software Engineer

Engineering San Francisco On-site Full time Compensation $170K – $300K $40K – $120K Equity Up to $25K in relocation assistance We want to build agents that autonomously validate code changes. Today that looks like AI that reviews pull requests in GitHub, catching bugs and enforcing standards. Greptile reviews 5B lines of code every month for 22,000+ customers. Problems we’re excited about Coding standards can be idiosyncratic and are often poorly documented; can we build agents that learn them through osmosis like a new hire might? Can we identify for each customer what types of PR feedback they do and don’t care about, perhaps using some sample efficient RL, in order to increase signal-to-noise ratio? Some bugs are best caught by running the code, potentially against discerning AI-generated E2E tests. Can we autonomously deploy feature branches and use agents to parallel try to break the application to detect bugs? Trajectory 22,000+ customers 5B lines of code reviewed every month Scaled from $0 to eight figures in ARR Raised $30M from Benchmark, Y Combinator, Paul Graham, and Initialized Team We have assembled a small, talent dense team who have scaled critical functions at companies like Stripe, Google, Figma, etc. Responsibilities (in order of how much time you’ll likely spend on each) Solve some of our hardest and most interesting problems, including LLM memory, multi-language codebase indexing, semantic search for large codebases, and much more. Design, implement, test, and deploy full features Get user feedback to iterate the features Qualifications B.S. Computer Science or equivalent degree, undergraduate or higher 1+ years of software or DevOps engineering experience Experience with JavaScript/TypeScript You will like this role if You want to work on a product that thousands of developers rely on The chaos of high growth and things breaking is exciting to you You like being in an office every day around other smart people who are excited about what they’re building You love solving very hard problems. You specifically prefer working in-person over working remote