Senior Engineering Manager, Marketplace

Upstart is a leading AI lending marketplace focused on reducing the cost and complexity of borrowing for Americans. The Engineering Manager for Marketplace Optimization will lead engineering teams to develop scalable systems that enhance marketplace outcomes and collaborate with cross-functional teams to ensure high-quality delivery.

Responsibilities:

• Define and execute the team’s technical roadmap: deliver matching, offer-selection, monetization, and target-return logic and features that improve marketplace outcomes
• Build and grow a high-performing engineering team: hire, mentor, and develop engineers and ICs; establish clear expectations and career growth paths
• Drive technical excellence: own architecture and delivery decisions for scalable, fault-tolerant services, data pipelines, and APIs that integrate with ML models and capital systems
• Collaborate cross-functionally with Product, ML, Capital Markets, and Risk to translate business goals into prioritized, measurable engineering work
• Own operational reliability and observability: establish SLOs/SLIs, alerting, runbooks, and post-incident practices to ensure marketplace integrity and fast incident response
• Lead delivery and execution: unblock teams, manage technical and organizational risks, and ensure high-quality, timely releases while balancing speed and safety

Requirements:

• 8+ years of software engineering experience, with 3+ years in an engineering manager role (managing individual contributors and/or managers)
• Proven success leading and scaling high-performing engineering teams (e.g., growing headcount, improving delivery metrics, or managing multiple squads)
• Demonstrated domain expertise in marketplace optimization, pricing/fee/monetization, or routing systems at scale
• Demonstrated ability to partner closely with Product, and ML teams to deploy models at scale and build scalable production ready systems
• Exceptional communication skills with the ability to influence technical and non-technical audiences
• Strong analytical, organizational, and strategic thinking skills with a bias for action
• Hands-on familiarity with cloud platforms (AWS/GCP/Azure), containerization and orchestration (Docker/Kubernetes), and scalable API design
• Experience with streaming and event architectures (e.g., Kafka, Pub/Sub) and modern data platforms
• Track record operating in regulated or compliance-sensitive environments and building systems that support auditability
• Background in statistics, economics, or applied ML domains
• Demonstrated success building observability and reliability practices (SLO/SLI design, monitoring, alerting, post-incident process) and scaling engineering processes across multiple teams