$600B is spent on cloud each year, but no one knows the cost until it's too late. We’re changing that.

Since launching Infracost in 2021, we’ve been pulled by engineers who all want to Shift FinOps Left. We enable them to proactively find and fix cloud cost issues before they hit production. We plug directly into developer workflows (like GitHub and Azure Repos), show cost impact in pull requests, enforce tagging and FinOps best practices, and even generate PRs to fix issues automatically.

We're backed by Sequoia, YC and trusted by Fortune 500 enterprises. You'll join a small, experienced, and supportive team that's shipping fast, solving real infrastructure problems, and having fun while doing it.

Whether you're an engineer tackling complex systems (e.g. parsing massive Terraform repos, scaling real-time systems), a product manager shaping strategy from real customer pain points, or a customer success lead working directly with users; there’s meaningful work here for you. If you care about cloud efficiency, great UX, and helping teams move faster and smarter, we’d love to work with you!

Parse chaos into structure. You’ll help build the engine that analyse and fix infrastructure across thousands of codebases. You’ll ship fast, and work with other engineers to dig deep into weird bugs and performance issues.

What we’re looking for:

• GMT+2 to GMT-6 time zone
• Strong Golang (or equivalent) experience. You write idiomatic, concurrent code, can track down where the memory leaks are, and debug race-conditions.
• You move fast. You get a dopamine hit every time you release to production, and jump on issues without hesitation.
• You've built something from scratch that you're proud of.
• You’ll thrive in an amazing, experienced, hardworking, respectful, supportive, and fun team.
• (Preferred) Familiarity with Terraform, Kubernetes, and AWS for infrastructure management. We use these tools and so do our customers.

Examples of challenges we have worked on recently:

• Built the best-in-class Terraform static analysis engine. We needed a way we could parse massive Terraform mono-repos as quickly as possible, able to handle tens of thousands of module downloads, as well as gracefully handling incomplete data.
• Scaled to support customers with thousands of GitHub organizations and tens of thousands of repositories. W’eve overhauled our APIs, interfaces, onboarding processes, infrastructure, and more.
• Automatically fixing infrastructure issues. With infrastructure changes there's a lower tolerance for AI-generated slop - there's not the same safety nets in terms of testing and the risk is often higher. We've been iterating on our system that combines the AI-generated changes with our best-in-class static analysis engine to robustly open good-quality PRs to fix the most important issues for our customers.

What we value:

1. Ustomer, not customer: It is all about seeing us and the customer as one. We like to be a part of the user’s team, and help them however we can. If the user is not successful, then we will not be either so we try to walk in their shoes. It's more than work - we build relationships and community with users and customers.
2. Open is our core: Put yourself out there. Show your learning. Transparency builds confidence. Encourage sharing the good and the bad. The best decisions are made when everyone has access to all the data. Be straightforward and kind, feedback is about your work not your person.
3. Let's JEDI: Let’s Just Effing Do It! Own it and move fast. A good plan fiercely executed now is better than a perfect plan later. We ask for help and unblock each other. The main thing, is to keep the main thing, the main thing.

Benefits:

• Fully remote team
• Two meetups a year - last year we went to Croatia and Barcelona.
• Employee-friendly equity terms, including a 10 year exercise window
• 401k matching (US)
• Health, dental, and vision insurance (US)
• 31 days paid vacation (includes national holidays)
• 12 weeks paid parental leave

Go, TypeScript, Node.js, React, PostgreSQL, Kubernetes, AWS

Our recent technical challenges

• Built the best-in-class Terraform static analysis engine. We needed a way we could parse massive Terraform mono-repos as quickly as possible, able to handle tens of thousands of module downloads, as well as gracefully handling incomplete data.
• Scaled to support customers with thousands of GitHub organizations and tens of thousands of repositories. W’eve overhauled our APIs, interfaces, onboarding processes, infrastructure, and more.
• Automatically fixing infrastructure issues. With infrastructure changes there's a lower tolerance for AI-generated slop - there's not the same safety nets in terms of testing and the risk is often higher. We've been iterating on our system that combines the AI-generated changes with our best-in-class static analysis engine to robustly open good-quality PRs to fix the most important issues for our customers.