About the role: Ready to see the direct impact of your code on business results and customer lives?
Join our Collection team as a Software Engineer and help shape the future of debt recovery at CloudWalk!
You'll be building end-to-end collection journeys that maximize debt recovery while maintaining an exceptional customer experience.
This role combines technical excellence with AI-powered solutions to accelerate delivery and drive measurable impact.
Build & Scale: Develop intelligent, scalable solutions for collection journeys that handle high-volume debt recovery operations.
Design Customer-Centric Experiences: Create comprehensive renegotiation and installment strategies that balance recovery goals with customer satisfaction.
Leverage AI for Impact: Use artificial intelligence to prioritize tasks, automate workflows, and accelerate feature delivery.
Collaborate & Iterate: Work cross-functionally with Product, Data, and Customer Success teams to test and implement recovery strategies.
Measure & Optimize: Analyze customer behavior data to measure impact and continuously iterate on collection approaches.
Love Building Backend Solutions: Have solid software development experience with backend technologies, preferably Python (though we're open to other backend languages too).
Embrace AI & Automation: Are familiar with generative AI tools and models, ready to integrate them into real-world applications.
Are Genuinely Curious: Have authentic interest in credit, collections, and debt recovery domains—you want to understand the business impact.
Drive Results: Are impact-oriented with a focus on solving real problems and delivering measurable outcomes.
Thrive in Fast-Paced Environments: Can balance technical excellence with urgency and customer-first thinking.
Advanced/fluent english for communication
Fintech Experience: Previous work in credit, collections, or financial services.
Analytics Skills: Comfort with data analysis tools and the ability to derive insights from customer behavior patterns.
AI/ML Background: Experience building or deploying machine learning models in production environments.
