Staff Generalist Engineer

Drive Capital; San Francisco (CA); On-site; USD 120,000 - 190,000; Full time

Job summary

Greptile in San Francisco is seeking a Staff Generalist Engineer to tackle some of our most challenging problems in AI-assisted code review. You will design, implement, test, and deploy full features, from memory models to multi-language indexing, with attention to reliability and performance.

You’ll collaborate with a small, high-signal team, gather user feedback, set architectural direction, and help scale systems as Greptile grows in a fast-paced, in-person environment.

Qualifications

• B.S. Computer Science or equivalent degree (undergraduate or higher).
• 6+ years of software or DevOps engineering experience.
• Experience with JavaScript/TypeScript.

Responsibilities

• 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
• Lead cross-team initiatives that span multiple quarters
• Set architectural direction and technical standards while simplifying complex systems
• Build platforms, tooling, and shared infrastructure that make the entire team faster
• Proactively manage risk across scaling, incidents, security, and compliance

Skills

JavaScript/TypeScript

Education

B.S. Computer Science or equivalent degree, undergraduate or higher

Job description

Staff Generalist Engineer

Greptile is an AI code reviewer that catches bugs and anti-patterns in pull requests with complete context of the codebase. Hundreds of top software companies, from YC startups to big tech, and teams in finance, healthcare, and defense, use Greptile to merge PRs faster and catch more bugs.

Greptile reviews 5B lines of code every month for 22,000+ customers. A new repo starts using Greptile every 2 minutes. We also uniquely offer self-hosted, air-gapped deployments for enterprises across defense, financial services, and healthcare.

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

• Lead cross-team initiatives that span multiple quarters

• Set architectural direction and technical standards while simplifying complex systems

• Build platforms, tooling, and shared infrastructure that make the entire team faster

• Proactively manage risk across scaling, incidents, security, and compliance

Qualifications

• B.S. Computer Science or equivalent degree, undergraduate or higher

• 6+ 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