About The Role

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?

We have assembled a small, talent dense team who have scaled critical functions at companies like Stripe, Google, Figma, etc.

Own and ship growth-critical engineering projects end-to-end, from identifying opportunities to building, launching, and iterating based on results
Design, build, and run experiments across the full user journey, spanning the marketing website, onboarding, activation, and product interactions
Partner closely with product and growth teams to scope ideas and ship high-quality, production-ready implementations
Build and own the core analytics and attribution framework, including event instrumentation, dashboards, and reporting used to guide decisions
Define and track clear success metrics (e.g. activation, conversion, retention), and use data to decide what to double down on or stop
Work across the stack (frontend, backend, and data) to ship pragmatic solutions that meaningfully move key metrics
Balance fast, iterative experimentation with higher-conviction projects, owning technical execution in both cases

Strong software engineering foundation (frontend, backend, or full-stack)
Experience building and shipping user-facing product or web features
Comfort working with data, metrics, and experimentation to inform decisions
Solid product intuition and curiosity about how users discover, adopt, and stick with products
Ability to move quickly, take ownership, and learn through iteration without sacrificing code quality
Familiarity with modern web stacks and analytics tooling
Interest in how products grow across channels (e.g. paid acquisition, SEO, lifecycle email), and eagerness to learn how engineering decisions shape outcomes
Bonus: experience with developer tools, product-led growth, or B2B SaaS