Backed by Y Combinator.
About the role
Cogentiq I2C is Fractal’s agentic AI Product for invoice-to-cash, covering Collections, Cash Application, Deductions, Invoice Management and Credit Risk. It runs on a Next.js front end, a FastAPI service layer, the Cogentiq agentic runtime, and a data tier on Azure Databricks with PostgreSQL.
What they're looking for
- Ten to fourteen years building software, with at least three leading a team or a full product build
- Track record of owning technical design for a product, not only implementing someone else’s design
- Deep expertise in at least one tier, and enough working command of the others to lead, review and debug across all of them
- Strong Python, and production experience with FastAPI or an equivalent service framework
- Practical experience of a modern front end, typically React or Next.js, enough to hold the standard even if you are not the primary developer
- Data engineering depth: Spark and Databricks, Delta Lake, SQL, and sound judgement on what belongs in a lakehouse and what belongs in PostgreSQL
More about this role
It's fun to work in a company where people truly BELIEVE in what they are doing!
We're committed to bringing passion and customer focus to the business.
Cogentiq I2C is Fractal’s agentic AI Product for invoice-to-cash, covering Collections, Cash Application, Deductions, Invoice Management and Credit Risk. It runs on a Next.js front end, a FastAPI service layer, the Cogentiq agentic runtime, and a data tier on Azure Databricks with PostgreSQL.
The product is led by two engineering leads at the same level. One owns the AI side: agents, models and everything that makes them work. You own the engineering side: the application, the services, the data and the platform they run on. You design it, you lead the team that builds it, and you write code yourself.
- Technical design of the engineering side, including the platform decisions that shape what can be built later.
- Delivery across the front end, the service layer, the data tier and the infrastructure they run on.
- The interfaces between your side and the agent runtime, agreed jointly with the AI Lead.
- Technical quality: code review standards, testing, performance, and the trade-offs taken to hit a date.
- Engineering health:...
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