Why this company

We are building the system of record for how mid-market finance teams close their books, and AI is changing what that work looks like. We have strong product-market fit with finance teams at fast-growing companies, a leadership team that has scaled infrastructure before, and the backing to keep investing. The work is ambitious, the bar is high and the chance to define a new category is real.

Our team moves quickly, takes ownership and stays close to customers. We hold to three ideas: act on clear judgment rather than perfect information, choose the simple option because it scales, and finish what we start.

Role overview

As a Staff Software Engineer on the Infrastructure team, you will own the reliability, security and performance of the platform finance teams depend on every day. You will sit at the intersection of infrastructure and product, running the systems that keep us fast, secure and always on across multiple cloud regions, and building the tools that let every other engineer ship with confidence.

What you'll do

• Design and run Kubernetes based infrastructure across regions, with a focus on reliability and cost.
• Own infrastructure as code, deployment pipelines and the developer platform other teams build on.
• Define service level objectives, on call practices and incident response, and lead post incident reviews.
• Build observability that lets engineers find and fix problems in minutes.
• Partner with security on compliance work and customer security reviews.
• Mentor engineers and set technical direction for the infrastructure roadmap.

What you have

• Eight or more years in software or infrastructure engineering, with deep experience running production systems on AWS, GCP or Azure.
• Strong hands-on skills with Kubernetes, Terraform or similar tools, CI/CD and observability.
• Experience being on call for a system at scale and making it measurably better.
• Comfort writing code in Go, Python or TypeScript.
• The ability to decide with incomplete information and explain trade offs to technical and non technical teammates.

Nice to have

• Experience with data platforms or AI workloads, such as GPU scheduling and model serving.
• Experience at a company that grew from tens to hundreds of engineers.

Compensation

Compensation includes base salary, equity and a full benefits package.