Software Engineer II, Verifications Decisioning

Upstart is a leading AI lending marketplace focused on reducing borrowing costs and complexity for Americans. The Software Engineer II will build and scale backend services for automated approval decisions, verification workflows, and fraud detection systems, while collaborating cross-functionally 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