Software Engineer II, Verifications Decisioning

Upstart is a company focused on building backend platforms for automated verification and fraud detection across lending products. As a Software Engineer II, you will design and develop backend services to enhance automated approval decisions and verification workflows while collaborating with cross-functional teams to optimize the verifications journey.

Responsibilities:

• Design and build backend services that power verification orchestration, risk evaluation, and automated approval decisions
• Develop and evolve rule engines and decisioning systems to increase automation coverage across products
• Integrate external data providers (e.g., Plaid) into resilient, scalable workflows
• Improve document automation pipelines including classification, extraction, and fraud detection systems
• Build and maintain APIs, Kafka events, and service contracts that enable product teams to consume verification capabilities
• Partner with ML engineers to productionize risk models and ensure decision correctness at scale
• Contribute to platformization efforts to standardize Verifications stages and enable cross-product reuse
• Strengthen compliance, data integrity, and observability across verification systems

Requirements:

• 4+ years of professional software engineering experience
• Experience designing and building scalable backend systems in languages such as Java, Kotlin, Go, or Python
• Experience developing and operating distributed systems, including service-to-service APIs and event-driven architectures
• Experience contributing to a decision engine that integrates with machine learning models to evaluate signals
• Experience writing production-quality code with testing and monitoring
• Bachelor's degree in Computer Science or equivalent practical experience
• Experience building rule engines, decisioning systems, or risk evaluation platforms
• Experience working with financial services, lending, fraud detection, or identity verification systems
• Experience integrating third-party APIs and external data providers
• Familiarity with workflow orchestration systems (e.g., Temporal)
• Experience working with Kafka or event-driven systems
• Exposure to ML model integration in production systems