The Team:

Marketplace Optimization builds the intelligent systems that power Upstart's AI lending marketplace. Our teams make real-time decisions about how borrowers are matched with capital, how offers are constructed, and how the marketplace evolves through experimentation. We solve complex optimization problems at scale, balancing borrower experience, investor objectives, profitability, and operational efficiency while operating some of the most critical services at Upstart.

Within Marketplace Optimization, engineers join one of two closely related teams:

• Monetization builds the marketplace services that optimize marketplace economics through origination fees, offer construction, and experimentation capabilities that allow the business to rapidly evolve monetization strategies.
• Matching & Offer Selection builds the real-time decision engine that intelligently matches borrowers with capital providers while balancing borrower outcomes, investor commitments, marketplace efficiency, and business objectives.

As a Senior Software Engineer, you'll partner closely with Product, Machine Learning, Pricing, Capital Markets, Lending Partnerships, and Analytics to build highly reliable distributed systems that power millions of lending decisions. You'll work on systems at the heart of Upstart's lending marketplace. The software your team builds determines how borrowers are matched with capital, how offers are constructed, and how marketplace decisions are executed in real time. It's an opportunity to solve challenging distributed systems problems while building software with direct, measurable impact on borrowers, investors, and the business.

How you’ll make an impact

• Design, build, and operate highly available backend services that power Upstart's real-time lending marketplace.
• Develop scalable systems that enable rapid experimentation while maintaining the reliability of business-critical production services.
• Partner with Product, Machine Learning, Capital Markets, and Analytics to translate complex business problems into elegant technical solutions.
• Build flexible platform capabilities that enable new marketplace optimization and monetization strategies.
• Improve the scalability, observability, and operational excellence of systems responsible for real-time marketplace decisions.
• Participate in architecture discussions, code reviews, testing, and operational ownership of critical production systems.

Minimum Qualifications

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent practical experience)
• 5+ years of professional software engineering experience building backend or distributed systems
• Experience developing production services using one or more of Ruby on Rails, Python, or Kotlin
• Experience designing APIs and building scalable distributed systems
• Experience operating business-critical production services with an emphasis on reliability, monitoring, testing, and operational excellence
• Experience with cloud platforms (AWS preferred) and modern cloud-native application development
• Experience collaborating across engineering, product, and business stakeholders

Preferred Qualifications

• Experience building marketplaces, recommendation systems, optimization engines, financial systems
• Experience with event-driven architectures, Kafka, workflow orchestration, or real-time data processing
• Experience partnering with Machine Learning or Data Science teams
• Experience improving platform scalability and evolving distributed system architecture
• Interest in solving complex optimization problems that combine technical and business tradeoffs

Position location This role is available in the following locations: Remote

Time zone requirements The team operates on the East/West coast time zones.

Travel requirements As a digital first company, the majority of your work can be accomplished remotely. The majority of our employees can live and work anywhere in the U.S or Canada (outside of Quebec) but are expected to spend high quality time in-person collaborating via regular onsites and in-person meetings. The onsite cadence varies depending on the team and role; most teams meet once or twice per quarter for 2-4 consecutive days at a time.