Description:

The Consumer Risk team is responsible for protecting Plaid and its ecosystem against fraud and abuse activities by building risk defense solutions and capabilities to detect and mitigate abuse across all Plaid products.
You will develop risk defenses to help Plaid detect and mitigate abusive activities across products.
You will build tailored risk systems and work with product teams to implement defenses that benefit the broader ecosystem.
You will partner with data scientists, machine learning engineers, product managers, and other cross-functional teams to derive risk insights, improve product features, and respond to fraud challenges across the ecosystem.
You will influence product direction to enhance resilience against fraud and abuse, solving complex problems by navigating organizational and technical challenges with innovative solutions.
You will be responsible for ensuring success in the mission to protect Plaid’s products, consumers, and the broader ecosystem against fraud and abuse.
You will lead and directly contribute to the critical fraud domain, driving multi-quarter, cross-team, and cross-service technical projects.
You will gain extensive collaboration opportunities with cross-functional leaders across the company—including Risk, Security, Legal, GTM, and Beacon—helping to influence product strategies and directions across all Plaid products.
You will work to automate how operations teams review and respond to new or ongoing attacks.

Requirements:

You must have 6+ years of experience with extensive experience in software engineering with a proven track record of shipping successful projects.
You should have experience in the Fraud & Risk Engineering domain with hands-on experience building end-to-end risk solutions.
You need to possess excellent coding, testing, and system design skills.
You must have excellent analytical and problem-solving skills.
You should have experience working with product, design, data science, and machine learning.
It is a plus to have experience in productionizing machine learning models.
It is also a plus to have experience in shipping 0 to 1 projects.
Experience in data-intensive systems and graph data models is considered a nice to have.

The target base salary for this role is $182,520 - $297,000 per year.
Additional compensation in the form(s) of equity and/or commission are dependent on the position offered.
Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k).
Pay is based on factors such as the scope and responsibilities of the position, the candidate's work experience and skillset, and location.
Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.