Engineering at Brex

The Engineering team includes Data, IT, Security, and Software, and is responsible for building innovative products and infrastructure for both internal and external users. We have multiple autonomous and collaborative teams who are eager to learn, teach, and constantly improve how things work. Together, we strive to build robust and scalable systems that enable Brex to grow rapidly and help our customers reach their full potential.

What you’ll do

We are seeking individuals passionate about building data-driven systems to manage risk at scale. You will have significant exposure to every aspect of financial crime prevention, from building customer-facing experiences to working closely with data scientists to seamlessly integrate models into production. As Risk services interface with multiple systems across Brex, excellent interpersonal and written communication skills are essential. You will be working on high-impact projects requiring high development standards, handling and upkeeping the integrity of sensitive data, and ensuring compliance while driving monetary outcomes. In this role, you’ll gain specialized knowledge in risk management and contribute to building the most beloved financial services and softwares, all while safeguarding our customers, our platform, and the integrity of the financial market.

Where you’ll work

This role will be based in our San Francisco office. You must be willing to work in office at least 2 days per week on Wednesday and Thursday. Employees will be able to work remotely for up to 4 weeks per year, for a minimum of one week at a time.

Responsibilities

• Ensure that the data for our decisioning systems is always of the highest quality, utilizing best-in-class services (risk vendors and internal models) to provide actionable insights that drive risk management and customer experience improvements
• Develop low-latency decision systems for assessing risk during customer onboarding, payments, authentication, and in-app
• Build in-product levers that enhance our decisioning systems while striving to make risk management invisible
• Build systems and tools for comprehensive customer due diligence, including KYC, sanctions, adverse media, PEP, and AML monitoring

Requirements

• 4+ years of professional experience in a software engineering role or equivalent experience 
• Strong fundamental knowledge in at least one of the following: machine learning theory or systems  
• Experience building and designing scalable decisioning systems 
• Experience working with backend programming languages (Kotlin, Python)
• Ability to hold yourself and the team to high standards
• Strong communication and interpersonal skills

Bonus points

• Publications or contributions to open-source projects related to data-intensive systems.
• Familiarity with algorithms for decision-making under uncertainty, including Bayesian networks, Markov decision processes, or reinforcement learning

Compensation

The expected salary range for this role is $192,000 - $240,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.