Pros
Small team, big product: The engineering team is lean relative to the size and complexity of the product, which means you can have real ownership and see your impact quickly.
Great staff-to-product ratio for the AI era: There’s enough headcount to move fast, experiment, and ship, without the layers of bureaucracy you see elsewhere. Using AI to boost coding productivity means the current team can reach into more markets and build more products without incurring additional cost.
Modern tooling and strong quality focus: This may differ from what other reviewers have mentioned, but my experience is that the company invests in up-to-date monitoring and delivery practices (e.g. Datadog, modern CI/CD pipelines) and has a clear focus on code quality and reliability.
Strong culture of integrity: Leadership consistently emphasizes doing things the right way, not the quick way. There’s no pressure to cut corners, and quality is genuinely valued.
Engineer-focused environment: This is a product- and engineering-driven company with essentially no “hard sell” culture. The focus is on building a strong product and letting that speak for itself.
Clear product vision in banking: The vision around event-driven, open, and connected banking is compelling. You get the sense that the company knows where it wants to go and why.
Cons
Legacy platform constraints: The core still runs heavily on IBM i, which makes some aspects of modernization and rapid iteration harder than they should be. It’s not a show-stopper, but it does introduce friction and can limit how fast new technologies are adopted.
Small team can be a double-edged sword: Ownership is great, but it also means context switching and wearing multiple hats. If you prefer narrow, specialized roles, this might feel overwhelming.