Software Engineer, Revenue Science

Software Engineer Revenue Science

• Title of Role: Software Engineer Revenue Science
• Location: remote
• Company Stage of Funding: Post-IPO Debt Financial Services
• Office Type: Remote
• Salary: To be confirmed with final candidates

Company Description

Were representing a pioneering AI-enabled lending marketplace that partners with financial institutions to enhance access to affordable credit. By leveraging non-traditional variables to assess creditworthiness this company is reshaping how credit is priced and accessed significantly expanding opportunities for underserved borrowers. Their innovative approach utilizes advanced data analysis and proactive borrower management to deliver a superior lending experience.

What You Will Do

• Design build and maintain scalable backend services and APIs that support capital markets and pricing operations.
• Develop and optimize data pipelines and event-driven architectures for real-time financial data processing.
• Collaborate with engineering data science and finance teams to enhance infrastructure that supports lending marketplace operations.
• Contribute to cloud-native system design and deployment across distributed environments.
• Work with SQL databases and data warehousing solutions to facilitate financial reporting and analytics.
• Scale internal tooling and infrastructure to improve operational efficiency and visibility.
• Solve complex real-world problems while ensuring high standards for reliability and performance.

Ideal Candidate Background

• 35 years of professional software engineering experience with a backend focus.
• Proven experience with distributed systems APIs and event-driven architectures.
• Proficiency in Kotlin or Python with strong SQL/Postgres expertise.
• Hands-on experience in cloud-native environments (AWS GCP or Azure).
• Experience building and maintaining real-time data pipelines or stream processing tools.

Preferred

• Background in fintech particularly in capital markets pricing systems or financial operations.
• Experience integrating machine learning models into production systems.
• Interest in or experience with internal tooling or infrastructure.

Compensation and Benefits

This company offers a flexible digital-first work environment with competitive compensation and innovative equity options designed to reward your contributions from day one.

Required Experience:

IC