Senior Software Engineer, Risk

Our mission

The trucking and logistics industry provides the backbone of the economy. But the payments infrastructure on which it runs is broken. For the hard-working men and women of this sector, the existing suite of payment tools is outdated, difficult to use, prone to fraud, and saddled with shady fee structures. The incumbent players in this space often overlook the economic and practical needs of this user base.

We're changing that. AtoB is building Stripe for Transportation — modernizing the payments infrastructure for trucking and logistics. Supply chains rely on the timely movement of capital to function efficiently. Our end game is a world in which that capital movement occurs fairly, smoothly, and without delay. As we pursue that end game, we aim to center our customers in every way — offering them world-class customer experience and building products that work with and around the unique constraints of their daily lives. We build for fleet managers in the office and drivers on the road. We strive for products that are efficient, satisfying, and useful. Our customers enable our modern economy — they deserve it.

Responsibilities

1. Help build the platform that allows AtoB to verify and underwrite new customers and identify and prevent fraudulent behavior and coordinated attacks.
2. Create and improve machine learning models that score customers for creditworthiness and loss risk and determine other risk-related factors.
3. Partner with various Risk and Product teams including analysts, business operations, and underwriters to create strategy, vision, and the goals for managing customer credit, transaction, and payment risk at AtoB.
4. Deliver robust technical solutions rapidly and iteratively.
5. Help define the technical roadmap for risk engineering.
6. Ensure we are making the right trade-offs between moving fast and holding a high-quality bar.

Who you are:

1. Have 4+ years of experience building B2B or B2C SaaS products, preferably in fintech or the financial services domain assessing risk and detecting fraud at scale.
2. Have solid experience in using machine learning and data transformation to deliver critical impact to the business.
3. Are self-motivated and relentlessly focused on delivering business value.
4. Enjoy thinking about systems and their life cycles, edge cases, interactions, and failure modes.
5. Strong sense of ownership and enjoy working on projects end-to-end in a fast-paced, high autonomy environment.