**About Finosu**
Finosu is an AI-native loan servicer. What is that? A servicer handles the communications and payment rails for lenders. The servicing industry services over 10 trillion dollars of debt a year.
Loan servicing is the perfect application for AI. Borrowers want help on their time, not during call center hours, and AI makes 24/7 support real for the first time. It also makes compliance better, not worse: every interaction follows the rules, every disclosure is delivered, and everything is logged and auditable. What makes us different is how we measure success. We are not judged on generic CSAT scores. We are judged on dollars generated for our lenders, and it turns out the two go together: borrowers who are treated well perform better.
We know this problem because we lived it. Our founders built a $200M consumer lender together, owning the end-to-end stack from origination through servicing and collections. We felt every broken part of it firsthand: the vendors that didn't care about outcomes, the compliance gaps, the borrowers who fell through the cracks. So we are building the thing we wished we had.
**Things to Know**
We are a start-up and our processes are in flux. Priorities might shift more abruptly than at a more establish company.
* We’re in office 5 days a week, we have found that collaboration especially in a context-rich field is important
* You will own client relationships that can scale to a million in ARR. Your job will be a mix between customer support and engineering to get the clients over the line. Examples include helping clients revise their own processes to accommodate AI, we’ve had clients need to slow down their outreach because of the success of our AI agents.
**About the Role**
This is a unique role in that we are looking for an engineer that will do anything to get a client over the line. At times, this is accommodating requests, and at other times, helping them make their processes more AI-native. We have a small team of less than 10 people.
In this role
* Figure how to integrate our systems with our client’s systems.
* You won’t always have the benefit of statistical significance, so intuition and taste will be important. For example, when examining best times to call, you won’t have data on a lender’s portfolio to guide your initial choices.
* 30/60/90
* 30 days: you will onboard a customer onto our platform. This will involve building client pipelines to map client’s schema to ours and vice versa.
* 60 days: you will work on capturing as much wallet share of ours clients by diving deeper and figuring out their bottlenecks in adapting to AI. For example, what hesitations do customers have about adopting AI, and where we can help alleviate it.
* 90 days: you will contribute back to our main system, and make changes that improve our technology for all our customers. For example, Python code to make sure we process all our payments as soon as possible to take advantage of bank opening windows.
Projects people in this role have taken or will take:
* Evaluate our AI agent architecture. We currently run Livekit on a pipeline stack: Deepgram, OpenAI, Cartesia. Since the field progresses so fast, we will need to develop internal benchmarks and figure out when to swap models in and out.
* Payment optimization. Our loan balance volume is in the millions of dollars. Our system will soon need proactive health checks to speed up our processing.
* Watching session replay to determine the best way to optimize our app.
About You
* We have a roadmap, but you’ll own your work: propose what to build, challenge priorities when you see a higher-impact path, and help the team ship what best serves our users.
* You learn quickly—aptitude and attitude matter more than years of experience.
* You love measuring things. As we move fast, the solutions to many challenges are hidden in the data.
* You’re product-minded and data-minded. In this role, you’ll make many decisions to build the best product across the projects you own.
Visa sponsorship is not available for this role.
