Software Engineer, Verifications Platform

Upstart is a leading AI lending marketplace on a mission to reduce the cost and complexity of borrowing for all Americans. The Software Engineer for the Verifications Platform will build and scale backend services that enable automated approval decisions and verification workflows, collaborating with various 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
• Build platform capabilities that enable reusable financial data connections across products while improving automation, observability, and connection lifecycle management
• Partner with underwriting, and verification teams to streamline Plaid data usage and accelerate the adoption of financial signals in decisioning models and automated workflows
• Collaborate with ML teams 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:

• Bachelor's degree in Computer Science and 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
• 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
• Experience working with financial data platforms, connection lifecycle management, or reusable data access systems
• Familiarity with systems that support multi-account, multi-product, or consent-aware financial data workflows