Risk & Fraud Software Engineer – Hybrid, Impactful Systems

Q2 India; United States; Hybrid; USD 110,000 - 150,000; Full time

Benefits offered by this job

Health & Wellness

Hybrid Work Opportunities

Flexible Time Off

Career Development

Parental Leave

Volunteer Programs

Employee Recognition

Job summary

Q2 is seeking a Software Engineer on the Risk & Fraud team to build production systems that detect and prevent fraud. You will design services, APIs, and data infrastructure, owning end-to-end delivery and reliability.

You will collaborate with product managers, data scientists, and engineers to translate fraud requirements into scalable solutions, while ensuring security and privacy policies are upheld.

Qualifications

• Bachelor's degree in a relevant field or equivalent experience.
• Proficiency in Python — well-tested, maintainable, scalable code.
• Proficiency in SQL and comfort with relational/analytic data stores.
• Proficiency in JavaScript/TypeScript and a modern framework (Vue.js or similar).
• Experience implementing and maintaining CI/CD pipelines.
• Experience building cloud-native, service-oriented architectures.

Responsibilities

• Design, implement, and test software solutions with high availability and resiliency.
• Build and operate scalable data workflows and data pipelines for fraud analytics.
• Work across the stack—from data layers to APIs to front-end integrations.
• Own systems end-to-end: delivery, monitoring, incident response, iteration.
• Collaborate with product managers, data scientists, and engineers on requirements.
• Ensure security, confidentiality and privacy compliance across systems.
• Mentor teammates and promote best engineering practices.

Skills

Python

SQL

JavaScript/TypeScript

CI/CD

Cloud-native

Education

Bachelor's degree in relevant field

Tools

Docker

Kubernetes

Airflow

dbt

Snowflake

AWS data services

Job description

Q2 is seeking a Software Engineer on the Risk & Fraud team to build production systems that detect and prevent fraud. You will design services, APIs, and data infrastructure, owning end-to-end delivery and reliability.

You will collaborate with product managers, data scientists, and engineers to translate fraud requirements into scalable solutions, while ensuring security and privacy policies are upheld.